Computer Science › Artificial Intelligence

Multi-Agent Systems and Negotiation

Works Count: 42594

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Description

This cluster of papers focuses on methods and techniques for agent-based modeling, encompassing topics such as multi-agent systems, argumentation frameworks, software engineering, simulation, negotiation, artificial intelligence, dialectical argumentation, formal methods, and social simulation.

Keywords

Agent-Based Modeling; Multi-Agent Systems; Argumentation Frameworks; Software Engineering; Simulation; Negotiation; Artificial Intelligence; Dialectical Argumentation; Formal Methods; Social Simulation

Modality and the English Modals

2014-02-04

Frank Palmer

Preface 1. Introduction 2. A basic framework 3. Epistemic modality 4. Deontic modality 5. Dynamic possibility 6. Dynamic necessity 7. Will, shall and futurity 8. Conditionals 9. Further issues References … Preface 1. Introduction 2. A basic framework 3. Epistemic modality 4. Deontic modality 5. Dynamic possibility 6. Dynamic necessity 7. Will, shall and futurity 8. Conditionals 9. Further issues References Indexes

Modeling rational agents with a BDI-architecture

1997-10-01

Anand S. Rao , Michael Georgeff

Rules of encounter: designing conventions for automated negotiation among computers

1994-08-23

Jeffrey S. Rosenschein , Gilad Zlotkin

Part 1 Machines that make deals: the premise machine encounters social engineering for machines scenarios how does this differ from Al? how does this differ from game theory? Part 2 … Part 1 Machines that make deals: the premise machine encounters social engineering for machines scenarios how does this differ from Al? how does this differ from game theory? Part 2 Interaction mechanisms: the negotiation problem in different domains attributes of negotiation mechanisms assumptions incentive compatibility. Part 3 Task-oriented domains: domain definition attributes and examples a negotiation mechanism evaluation of the negotiation mechanism an alternative, one-step protocol mechanisms that maximize the product of utilities the bottom line. Part 4 Deception-free protocols: non-manipulable negotiation mechanisms probabilistic deals subadditive domains concave domains modular domains summary of incentive compatible mechanisms the bottom line. Part 5 State-oriented domains: side-effects in encounters domain definition attributes and examples a negotiation mechanism worth of a goal conflict resolution semi-co-operative deals in non-conflict situations unified negotiation protocols (UNP) multi-plan deals the hierarchy of deal types - summary unbounded worth of a goal - tidy agents the bottom line. Part 6 Strategic manipulation: negotiation with incomplete information incomplete information about worth of goals using the revelation principle to re-design the mechanisms the bottom line. Part 7 Worth-oriented domains: goal relaxation domain definition one agent best plan negotiation over sub-optimal states examples of worth functions the bottom line. Appendices: strict/tolerant mechanisms some related work proofs.

Agent technology: foundations, applications, and markets

1998-04-01

Nicholas R. Jennings , Michael Wooldridge

Towards Flexible Teamwork

1997-09-01

M. Tambe

Many AI researchers are today striving to build agent teams for complex, dynamic multi-agent domains, with intended applications in arenas such as education, training, entertainment, information integration, and collective robotics. … Many AI researchers are today striving to build agent teams for complex, dynamic multi-agent domains, with intended applications in arenas such as education, training, entertainment, information integration, and collective robotics. Unfortunately, uncertainties in these complex, dynamic domains obstruct coherent teamwork. In particular, team members often encounter differing, incomplete, and possibly inconsistent views of their environment. Furthermore, team members can unexpectedly fail in fulfilling responsibilities or discover unexpected opportunities. Highly flexible coordination and communication is key in addressing such uncertainties. Simply fitting individual agents with precomputed coordination plans will not do, for their inflexibility can cause severe failures in teamwork, and their domain-specificity hinders reusability. Our central hypothesis is that the key to such flexibility and reusability is providing agents with general models of teamwork. Agents exploit such models to autonomously reason about coordination and communication, providing requisite flexibility. Furthermore, the models enable reuse across domains, both saving implementation effort and enforcing consistency. This article presents one general, implemented model of teamwork, called STEAM. The basic building block of teamwork in STEAM is joint intentions (Cohen & Levesque, 1991b); teamwork in STEAM is based on agents' building up a (partial) hierarchy of joint intentions (this hierarchy is seen to parallel Grosz & Kraus's partial SharedPlans, 1996). Furthermore, in STEAM, team members monitor the team's and individual members' performance, reorganizing the team as necessary. Finally, decision-theoretic communication selectivity in STEAM ensures reduction in communication overheads of teamwork, with appropriate sensitivity to the environmental conditions. This article describes STEAM's application in three different complex domains, and presents detailed empirical results.

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Kasbah: An Agent Marketplace for Buying and Selling Goods

1997-01-01

Anthony Chavez , Pattie Maes

While there are many Web services which help users find things to buy, we know of none which actually try to automate the process of buying and selling. Kasbah is … While there are many Web services which help users find things to buy, we know of none which actually try to automate the process of buying and selling. Kasbah is a system where users create autonomous agents to buy and sell goods on their behalf. In this paper, we describe how Kasbah works. We also discuss the implementation of a simple proof-of-concept prototype.

Probabilistic Robotics (Intelligent Robotics and Autonomous Agents)

2005-09-01

Sebastian Thrun , Wolfram Burgard , Dieter Fox

Introduction to Multi-Agent Systems

2009-01-01

Maja Hadzic , Pornpit Wongthongtham , Tharam S. Dillon +1 more

An Introduction to Multi-Agent Systems

2010-01-01

P. Balaji , Dipti Srinivasan

Software agents: an overview

1996-09-01

Hyacinth S. Nwana

Abstract Agent software is a rapidly developing area of research. However, the overuse of the word “agent” has tended to mask the fact that, in reality, there is a truly … Abstract Agent software is a rapidly developing area of research. However, the overuse of the word “agent” has tended to mask the fact that, in reality, there is a truly heterogeneous body of research being carried out under this banner. This overview paper presents a typology of agents. Next, it places agents in context, defines them and then goes on, inter alia , to overview critically the rationales, hypotheses, goals, challenges and state-of-the-art demonstrators of the various agent types in our typology. Hence, it attempts to make explicit much of what is usually implicit in the agents literature. It also proceeds to overview some other general issues which pertain to all the types of agents in the typology. This paper largely reviews software agents, and it also contains some strong opinions that are not necessarily widely accepted by the agent community.

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The vision of autonomic computing

2003-01-01

Jeffrey O. Kephart , David M. Chess

A 2001 IBM manifesto observed that a looming software complexity crisis -caused by applications and environments that number into the tens of millions of lines of code - threatened to … A 2001 IBM manifesto observed that a looming software complexity crisis -caused by applications and environments that number into the tens of millions of lines of code - threatened to halt progress in computing. The manifesto noted the almost impossible difficulty of managing current and planned computing systems, which require integrating several heterogeneous environments into corporate-wide computing systems that extend into the Internet. Autonomic computing, perhaps the most attractive approach to solving this problem, creates systems that can manage themselves when given high-level objectives from administrators. Systems manage themselves according to an administrator's goals. New components integrate as effortlessly as a new cell establishes itself in the human body. These ideas are not science fiction, but elements of the grand challenge to create self-managing computing systems.

The role of emotion in believable agents

1994-07-01

Joseph Bates

article Free Access Share on The role of emotion in believable agents Author: Joseph Bates Carnegie Mellon Univ., Pittsburgh, PA Carnegie Mellon Univ., Pittsburgh, PAView Profile Authors Info & Claims … article Free Access Share on The role of emotion in believable agents Author: Joseph Bates Carnegie Mellon Univ., Pittsburgh, PA Carnegie Mellon Univ., Pittsburgh, PAView Profile Authors Info & Claims Communications of the ACMVolume 37Issue 7July 1994 pp 122–125https://doi.org/10.1145/176789.176803Published:01 July 1994Publication History 698citation3,388DownloadsMetricsTotal Citations698Total Downloads3,388Last 12 Months138Last 6 weeks29 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

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Negotiation as a metaphor for distributed problem solving

1983-01-01

Randall Davis , Reid G. Smith

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Experiences creating three implementations of the repast agent modeling toolkit

2006-01-01

Michael North , Nicholson Collier , J. R. Vos

Many agent-based modeling and simulation researchers and practitioners have called for varying levels of simulation interoperability ranging from shared software architectures to common agent communications languages. These calls have been … Many agent-based modeling and simulation researchers and practitioners have called for varying levels of simulation interoperability ranging from shared software architectures to common agent communications languages. These calls have been at least partially answered by several specifications and technologies. In fact, Tanenbaum [1988] has remarked that the “nice thing about standards is that there are so many to choose from.” Tanenbaum goes on to say that “if you do not like any of them, you can just wait for next year's model.” This article does not seek to introduce next year's model. Rather, the goal is to contribute to the larger simulation community the authors' accumulated experiences from developing several implementations of an agent-based simulation toolkit. As such, this article focuses on the implementation of simulation architectures rather than agent communications languages. It is hoped that ongoing architecture standards efforts will benefit from this new knowledge and use it to produce architecture standards with increased robustness.

Is It an agent, or just a program?: A taxonomy for autonomous agents

1997-01-01

Stan Franklin , Art Graesser

Negotiation decision functions for autonomous agents

1998-09-01

Peyman Faratin , Carles Sierra , Nicholas R. Jennings

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Agent-based software engineering

1997-01-01

Michael Wooldridge

The technology of intelligent agents and multi-agent systems is expected to alter radically the way in which complex, distributed, open systems are conceptualised and implemented. The paper considers the problem … The technology of intelligent agents and multi-agent systems is expected to alter radically the way in which complex, distributed, open systems are conceptualised and implemented. The paper considers the problem of building a multi-agent system as a software engineering enterprise. Three issues are focused on: how agents might be specified; how these specifications might be refined or otherwise transformed into efficient implementations; and how implemented agents and multi-agent systems might subsequently be verified, to show that they are correct with respect to their specifications. These issues are discussed with reference to a number of case studies. The paper concludes by setting out some issues and open problems for future research.

Agent-oriented programming

1993-03-01

Yoav Shoham

A new computational framework is presented, called agent-oriented programming (AOP), which can be viewed as a specialization of object-oriented programming. The state of an agent consists of components such as … A new computational framework is presented, called agent-oriented programming (AOP), which can be viewed as a specialization of object-oriented programming. The state of an agent consists of components such as beliefs, decisions, capabilities, and obligations; for this reason the state of an agent is called its mental state. The mental state of agents is described formally in an extension of standard epistemic logics: beside temporalizing the knowledge and belief operators, AOP introduces operators for obligation, decision, and capability. Agents are controlled by agent programs, which include primitives for communicating with other agents. In the spirit of speech act theory, each communication primitive is of a certain type: informing, requesting, offering, and so on. This article presents the concept of AOP, discusses the concept of mental state and its formal underpinning, defines a class of agent interpreters, and then describes in detail a specific interpreter that has been implemented.

Elements of a plan-based theory of speech acts

1979-07-01

Philip R. Cohen , C. Raymond Perrault

This paper explores the truism that people think about what they say. It proposes that, to satisfy their own goals, people often plan their speech acts to affect their listeners' … This paper explores the truism that people think about what they say. It proposes that, to satisfy their own goals, people often plan their speech acts to affect their listeners' beliefs, goals, and emotional states. Such language use can be modelled by viewing speech acts as operators in a planning system, thus allowing both physical and speech acts to be integrated into plans. Methodological issues of how speech acts should be defined in a plan-based theory are illustrated by defining operators for requesting and informing. Plans containing those operators are presented and comparisons are drawn with Searle's formulation. The operators are shown to be inadequate since they cannot be composed to form questions (requests to inform) and multiparty requests (requests to request). By refining the operator definitions and by identifying some of the side effects of requesting, compositional adequacy is achieved. The solution leads to a metatheoretical principle for modelling speech acts as planning operators.

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Sold!: auction methods for multirobot coordination

2002-10-01

Brian Gerkey , Maja J. Matarić

The key to utilizing the potential of multirobot systems is cooperation. How can we achieve cooperation in systems composed of failure-prone autonomous robots operating in noisy, dynamic environments? We present … The key to utilizing the potential of multirobot systems is cooperation. How can we achieve cooperation in systems composed of failure-prone autonomous robots operating in noisy, dynamic environments? We present a method of dynamic task allocation for groups of such robots. We implemented and tested an auction-based task allocation system which we call MURDOCH, built upon a principled, resource centric, publish/subscribe communication model. A variant of the Contract Net Protocol, MURDOCH produces a distributed approximation to a global optimum of resource usage. We validated MURDOCH in two very different domains: a tightly coupled multirobot physical manipulation task and a loosely coupled multirobot experiment in long-term autonomy. The primary contribution of the paper is to show empirically that distributed negotiation mechanisms such as MURDOCH are viable and effective for coordinating physical multirobot systems.

Agents that reduce work and information overload

1994-07-01

Pattie Maes

article Free Access Share on Agents that reduce work and information overload Author: Pattie Maes MIT Media Lab., Cambridge, MA MIT Media Lab., Cambridge, MAView Profile Authors Info & Claims … article Free Access Share on Agents that reduce work and information overload Author: Pattie Maes MIT Media Lab., Cambridge, MA MIT Media Lab., Cambridge, MAView Profile Authors Info & Claims Communications of the ACMVolume 37Issue 7July 1994 pp 30–40https://doi.org/10.1145/176789.176792Published:01 July 1994Publication History 26citation8,051DownloadsMetricsTotal Citations26Total Downloads8,051Last 12 Months137Last 6 weeks19 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

Persuasion in Practical Argument Using Value-based Argumentation Frameworks

2003-06-01

Trevor Bench‐Capon

In many cases of disagreement, particularly in situations involving practical reasoning, it is impossible to demonstrate conclusively that either party is wrong. The role of argument in such cases is … In many cases of disagreement, particularly in situations involving practical reasoning, it is impossible to demonstrate conclusively that either party is wrong. The role of argument in such cases is to persuade rather than to prove, demonstrate or refute. Following Perelman, we argue that persuasion in such cases relies on a recognition that the strength of an argument depends on the social values that it advances, and that whether the attack of one argument on another succeeds depends on the comparative strength of the values advanced by the arguments concerned. To model this we extend the standard notion of Argumentation Frameworks (AFs) to Value-based Argumentation Frameworks (VAFs). After defining VAFs we explore their properties, and show how they can provide a rational basis for the acceptance or rejection of arguments, even where this would appear to be a matter of choice in a standard AF. In particular we show that in a VAF certain arguments can be shown to be acceptable however the relative strengths of the values involved are assessed. This means that disputants can concur on the acceptance of arguments, even when they differ as to which values are more important, and hence that we can identify points for which persuasion should be possible. We illustrate the above using an example moral debate. We then show how factual considerations can be admitted to our framework and discuss the possibility of persuasion in the face of uncertainty and disagreement as to values.

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Argumentation in artificial intelligence

2007-05-11

Trevor Bench‐Capon , Paul E. Dunne

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Intelligent agents: theory and practice

1995-06-01

Michael Wooldridge , Nicholas R. Jennings

Abstract The concept of an agent has become important in both artificial intelligence (AT) and mainstream computer science. Our aim in this paper is to point the reader at what … Abstract The concept of an agent has become important in both artificial intelligence (AT) and mainstream computer science. Our aim in this paper is to point the reader at what we perceive to be the most important theoretical and practical issues associated with the design and construction of intelligent agents. For convenience, we divide these issues into three areas (though as the reader will see, the divisions are at times somewhat arbitrary). Agent theory is concerned with the question of what an agent is, and the use of mathematical formalisms for representing and reasoning about the properties of agents. Agent architectures can be thought of as software engineering models of agents; researchers in this area are primarily concerned with the problem of designing software or hardware systems that will satisfy the properties specified by agent theorists. Finally, agent languages are software systems for programming and experimenting with agents; these languages may embody principles proposed by theorists. The paper is not intended to serve as a tutorial introduction to all the issues mentioned; we hope instead simply to identify the most important issues, and point to work that elaborates on them. The article includes a short review of current and potential applications of agent technology.

Developing multiagent systems

2003-07-01

Franco Zambonelli , Nicholas R. Jennings , Michael Wooldridge

Systems composed of interacting autonomous agents offer a promising software engineering approach for developing applications in complex domains. However, this multiagent system paradigm introduces a number of new abstractions and … Systems composed of interacting autonomous agents offer a promising software engineering approach for developing applications in complex domains. However, this multiagent system paradigm introduces a number of new abstractions and design/development issues when compared with more traditional approaches to software development. Accordingly, new analysis and design methodologies, as well as new tools, are needed to effectively engineer such systems. Against this background, the contribution of this article is twofold. First, we synthesize and clarify the key abstractions of agent-based computing as they pertain to agent-oriented software engineering. In particular, we argue that a multiagent system can naturally be viewed and architected as a computational organization , and we identify the appropriate organizational abstractions that are central to the analysis and design of such systems. Second, we detail and extend the Gaia methodology for the analysis and design of multiagent systems. Gaia exploits the aforementioned organizational abstractions to provide clear guidelines for the analysis and design of complex and open software systems. Two representative case studies are introduced to exemplify Gaia's concepts and to show its use and effectiveness in different types of multiagent system.

Tropos: An Agent-Oriented Software Development Methodology

2004-03-06

Paolo Bresciani , Anna Perini , Paolo Giorgini +2 more

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Collaborative plans for complex group action

1996-10-01

Barbara J. Grosz , Sarit Kraus

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An agent-based approach for building complex software systems

2001-04-01

Nicholas R. Jennings

article Share on An agent-based approach for building complex software systems Author: Nicholas R. Jennings Univ. of Southampton, UK Univ. of Southampton, UKView Profile Authors Info & Claims Communications of … article Share on An agent-based approach for building complex software systems Author: Nicholas R. Jennings Univ. of Southampton, UK Univ. of Southampton, UKView Profile Authors Info & Claims Communications of the ACMVolume 44Issue 4April 2001pp 35–41https://doi.org/10.1145/367211.367250Published:01 April 2001Publication History 774citation5,714DownloadsMetricsTotal Citations774Total Downloads5,714Last 12 Months80Last 6 weeks10 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

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The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver

1980-12-01

Smith

The contract net protocol has been developed to specify problem-solving communication and control for nodes in a distributed problem solver. Task distribution is affected by a negotiation process, a discussion … The contract net protocol has been developed to specify problem-solving communication and control for nodes in a distributed problem solver. Task distribution is affected by a negotiation process, a discussion carried on between nodes with tasks to be executed and nodes that may be able to execute those tasks.

On agent-based software engineering

2000-03-01

Nicholas R. Jennings

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KQML as an agent communication language

1994-01-01

Tim Finin , Richard Fritzson , Don McKay +1 more

This paper describes the design of and experimentation with the Knowledge Query and Manipulation Language (KQML), a new language and protocol for exchanging information and knowledge. This work is part … This paper describes the design of and experimentation with the Knowledge Query and Manipulation Language (KQML), a new language and protocol for exchanging information and knowledge. This work is part of a larger effort, the ARPA Knowledge Sharing Effort which is aimed at developing techniques and methodology for building large-scale knowledge bases which are sharable and reusable. KQML is both a message format and a message-handling protocol to support run-time knowledge sharing among agents. KQML focuses on an extensible set of performatives, which defines the permissible "speech acts" agents may use and comprise a substrate on which to develop higher-level models of interagent interaction such as contract nets and negotiation. In addition, KQML provides a basic architecture for knowledge sharing through a special class of agent called communication facilitors which coordinate the interactions of other agents. The ideas which underlie the evolving design of KQML are currently being explored through experimental prototype systems which are being used to support several testbeds in such areas as concurrent engineering, intelligent design and intelligent planning and scheduling.

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Expert Systems and Probabilistic Network Models

1997-01-01

Enrique Castillo , José Manuel Azcona , Ali S. Hadi

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Letizia: an agent that assists web browsing

1995-08-20

Henry Lieberman

Letizia is a user interface agent that assists a user browsing the World Wide Web. As the user operates a conventional Web browser such as Netscape, the agent tracks user … Letizia is a user interface agent that assists a user browsing the World Wide Web. As the user operates a conventional Web browser such as Netscape, the agent tracks user behavior and attempts to anticipate items of interest by doing concurrent, autonomous exploration of links from the user's current position. The agent automates a browsing strategy consisting of a best-first search augmented by heuristics inferring user interest from browsing behavior.

Towards requirements-driven information systems engineering: the Tropos project

2002-09-01

Jaelson Castro , Manuel Kolp , John Mylopoulos

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Software agents

1994-07-01

Michael Genesereth , Steven P. Ketchpel

article Free Access Share on Software agents Authors: Michael R. Genesereth Stanford Univ., Stanford, CA Stanford Univ., Stanford, CAView Profile , Steven P. Ketchpel Stanford Univ., Stanford, CA Stanford Univ., … article Free Access Share on Software agents Authors: Michael R. Genesereth Stanford Univ., Stanford, CA Stanford Univ., Stanford, CAView Profile , Steven P. Ketchpel Stanford Univ., Stanford, CA Stanford Univ., Stanford, CAView Profile Authors Info & Claims Communications of the ACMVolume 37Issue 7July 1994 pp 48–ff.https://doi.org/10.1145/176789.176794Published:01 July 1994Publication History 810citation1,659DownloadsMetricsTotal Citations810Total Downloads1,659Last 12 Months41Last 6 weeks7 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

A Concise Introduction to Decentralized POMDPs

2016-01-01

Frans A. Oliehoek , Christopher Amato

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Agent-Oriented Software Engineering

1999-01-01

Nicholas R. Jennings

Rule-based expert systems: The mycin experiments of the stanford heuristic programming project

1985-07-01

William Swartout

Strategic Maneuvering in Argumentative Discourse

2010-04-29

Frans H. van Eemeren

In Strategic Maneuvering in Argumentative Discourse, Frans H. van Eemeren brings together the dialectical and the rhetorical dimensions of argumentation by introducing the concept of strategic maneuvering. Strategic maneuvering refers … In Strategic Maneuvering in Argumentative Discourse, Frans H. van Eemeren brings together the dialectical and the rhetorical dimensions of argumentation by introducing the concept of strategic maneuvering. Strategic maneuvering refers to the arguer’s continual efforts to reconcile aiming for effectiveness with being reasonable. It takes place in all stages of argumentative discourse and manifests itself simultaneously in the choices that are made from the topical potential available at a particular stage, in adaptation to audience demand, and in the use of specific presentational devices. Strategic maneuvering derails when in the specific context in which the discourse takes place a rule for critical discussion has been violated, so that a fallacy has been committed. Van Eemeren makes clear that extending the pragma-dialectical approach to argumentation by taking account of strategic maneuvering leads to a richer and more precise method for analyzing and evaluating argumentative discourse.

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Axiomatization and implementation via objections structures

2025-06-23

Aymeric Lardon , Stéphane González | Theory and Decision

A social network group decision-making method considering satisfaction and trust of experts under preference ordering environment

2025-06-20

Yuan Xu | Information Sciences

Negotiators Algorithm: A Novel Parameter-Free Metaheuristic Inspired by Human Negotiation Behaviour

2025-06-20

| International journal of intelligent engineering and systems

A default framework for fundamental rights impact assessment

2025-06-16

Miguel García-Godínez | AI and Ethics

Replacing AI Agents for Backend

2025-06-13

Basaveni Siri Mallika Rao , Sai Santosh Goud Bandari | INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT

Abstract—Creating modern applications using a heavy backend is a big task for developers. Front end can be created easily using scripting languages like HTML, CSS, java script, react frameworks etc. … Abstract—Creating modern applications using a heavy backend is a big task for developers. Front end can be created easily using scripting languages like HTML, CSS, java script, react frameworks etc. and many low code tools like WordPress, Figma, Bolt etc., but creating a fully working backend is a difficult part for developers, students or startups. Instead of writing thousands of lines of code we can build applications using AI agents. Sounds unreal right? But yes, it’s possible we can replace maximum of our backend logic using AI agents. Traditional backend development involves significant manual effort in writing, testing and maintaining code to support functionalities of backend such as authentication, database management, business logic and notifications. With emergence of AI and workflow orchestration platforms, we can see a high potential on how we can transform backend systems using these intelligent agents, with advancements in artificial intelligence and no-code orchestration platforms such as n8n, there is a drastic change where backend systems can be created, managed and evolved by AI agents. This paper explores how AI agents can transform backend development eliminating boilerplate code and introducing adaptive, scalable and intelligent architectures to design an application. Keywords—AI Agents, Backend Development, Workflow Automation, n8n, No-Code Platforms, Intelligent Systems, Application Architecture, Natural Language Processing, Low-Code Development, Large Language Models (LLMs), Orchestration Tools, Business Logic Automation, API Integration, Smart Workflows

Model-based Individual Learning for Competitive Agents

2025-06-13

Yinghui Pan , Fen Chen , Biyang Ma +2 more | Research Square (Research Square)

<title>Abstract</title> Competitive multiagent reinforcement learning is complicated since training individual agents' policies is highly coupled with the prediction of other agents' actions in the learning process. It is rather difficult … <title>Abstract</title> Competitive multiagent reinforcement learning is complicated since training individual agents' policies is highly coupled with the prediction of other agents' actions in the learning process. It is rather difficult for the subject agent to reason with their actions, which however is particularly useful when the subject agent fails to execute the policy. In this article, we propose a myopic modeling-to-adaptation (MTA) framework to cope with competitive agent learning from the perspective of individual agents. A subject agent first learns its baseline policy while maintaining a set of candidate models of other agents. After that, it adapts the policy when interacting with the other agents and predicting their behaviours from the candidate models. Theoretically, an infinite number of candidate models shall be considered. We adapt a value equivalence approach to compress the model space. The difficulty lies in computing value equivalence when there is no explicit representation of agents' policy. We develop a scenario-based technique to evaluate the value equivalence of their candidate models. We demonstrate the new framework with the value equivalence based model compression approach in multiple problem domains.

Heuristic algorithms for credulous and sceptical reasoning problems in abstract argumentation

2025-06-11

Matthias Thimm | Journal of Logic and Computation

Abstract We consider problems of credulous and sceptical reasoning in abstract argumentation under a variety of semantics and present algorithms for heuristically solving these, i.e. we present algorithms that do … Abstract We consider problems of credulous and sceptical reasoning in abstract argumentation under a variety of semantics and present algorithms for heuristically solving these, i.e. we present algorithms that do not necessarily always give the correct answer but are more performant than correct algorithms. Our algorithms are based on using grounded semantics as a proxy for deciding acceptability w.r.t. other semantics and on bounded search for defenders. We perform a comprehensive experimental evaluation that shows competitive performance of our approaches.

Embodied Multi-Agent Systems: A Review

2025-06-01

Zhuo Li , Weiran Wu , Yunlong Guo +2 more | IEEE/CAA Journal of Automatica Sinica

Heterogeneous-Agent Models

2025-06-01

| World Scientific lecture notes in economics and policy

The Role of Agentic Language in Mobilizing Election Candidate Support

2025-05-30

Jan Nikadon , Caterina Suitner , Tomaso Erseghe +4 more | Journal of Language and Social Psychology

Agency, pertaining to planning and executing actions, is a core feature of the political landscape. Our study examines the temporal dynamics of agentic language in political online discourse during the … Agency, pertaining to planning and executing actions, is a core feature of the political landscape. Our study examines the temporal dynamics of agentic language in political online discourse during the 2020 U.S. Congressional Elections, spanning 180 days before and after Election Day, and before the Capitol Hill riots. We coded 495,252 messages posted by Democratic and Republican candidates on Twitter for agentic language, which was more prevalent in tweets of politicians who won elections. Temporal analyses revealed increased agency as critical political events approached, whether a planned democratic event (Election Day) or a sudden disruptive protest (Capitol riots). The study enhances our understanding of the role of agency expression in political social media communication. Politicians may strive to evoke agency among voters to encourage political engagement, and voters may be cautioned by our results about this subtle (possibly unaware) manipulative strategy.

THE FIVE LEVELS OF AI AGENTS: FROM AUTOMATION TO AUTONOMY

2025-05-29

| WORLD SCIENTIFIC eBooks

Relational Structure of Conceptual Spaces

2025-05-28

Mark Burgin , José María Díaz Nafría | WORLD SCIENTIFIC eBooks

Reasoning and Argumentation

2025-05-28

Hugo Mercier | MIT Press eBooks

The argumentative functions of strategic questions in Portuguese parliamentary speeches

2025-05-28

Fabrizio Macagno | Linguistics Vanguard

Abstract A question is normally defined in linguistics considering its presumptive illocutionary function, namely eliciting an answer to acquire information. However, questions have several “nonstandard” functions beyond the information-seeking one. … Abstract A question is normally defined in linguistics considering its presumptive illocutionary function, namely eliciting an answer to acquire information. However, questions have several “nonstandard” functions beyond the information-seeking one. One of the most important uses of questions, almost neglected in contemporary literature, is the strategic one, consisting of altering the interlocutors’ commitment stores to support a specific viewpoint or challenge the opposite standpoint. However, what does this modification of commitments amount to, and how and why is it used in a discourse? This paper aims to analyze the variety of argumentative uses of different syntactic types of nonstandard interrogative utterances, focusing on the types of arguments they express and how they modify the commitments of the two parties. Through the analysis of the Portuguese corpus of parliamentary speeches of 2022 (ParlaMint 4.0), the most important argumentative functions that nonstandard questions play therein are presented and illustrated.

Negotiation of Refusal Practices and Metapragmatic Awareness

2025-05-24

Augmenting the action space with conventions to improve multi-agent cooperation in Hanabi

2025-05-24

F. Bredell , Herman A. Engelbrecht , J. C. Schoeman

Comparative Analysis of Open-Source Frameworks for Agentic AI Systems: Capabilities, Design Philosophies, and Development Experiences

2025-05-23

Jianzheng Shi , David Kuo Chuen Lee , Weibiao Xu +1 more

Research on Reinforcement Learning Methodologies for Large Language Models Using TRPO, PPO, and DPO

2025-05-22

Tae-Hyun Kim , Soo-Hyun Park

Multi-agent systems powered by large language models: applications in swarm intelligence

2025-05-21

Cristian Jimenez-Romero , Alper Yegenoglu , Christian Blum

This work examines the integration of large language models (LLMs) into multi-agent simulations by replacing the hard-coded programs of agents with LLM-driven prompts. The proposed approach is showcased in the … This work examines the integration of large language models (LLMs) into multi-agent simulations by replacing the hard-coded programs of agents with LLM-driven prompts. The proposed approach is showcased in the context of two examples of complex systems from the field of swarm intelligence: ant colony foraging and bird flocking. Central to this study is a toolchain that integrates LLMs with the NetLogo simulation platform, leveraging its Python extension to enable communication with GPT-4o via the OpenAI API. This toolchain facilitates prompt-driven behavior generation, allowing agents to respond adaptively to environmental data. For both example applications mentioned above, we employ both structured, rule-based prompts and autonomous, knowledge-driven prompts. Our work demonstrates how this toolchain enables LLMs to study self-organizing processes and induce emergent behaviors within multi-agent environments, paving the way for new approaches to exploring intelligent systems and modeling swarm intelligence inspired by natural phenomena. We provide the code, including simulation files and data at https://github.com/crjimene/swarm_gpt .

Semantic Analysis and Discourse Processing

2025-05-21

Xiaochun Cheng , Preethi Nanjundan , Jossy P. George

Esports MA - transaction documents

2025-05-20

Autonomous IoT Agents Powered by Generative Reasoning

2025-05-20

Nirup Kumar Reddy Pothireddy

The emergence of Generative Artificial Intelligence (GenAI) has unleashed its operational capabilities to bring about a revolution for many autonomous systems, especially those in the domain of the Internet of … The emergence of Generative Artificial Intelligence (GenAI) has unleashed its operational capabilities to bring about a revolution for many autonomous systems, especially those in the domain of the Internet of Things (IoT). This paper explores a new mechanism for promoting generative reasoning in autonomous IoT agents for dynamic, context-situated planning and decision-making. The agents use generative models to simulate highly intricate emerging scenarios of the environment and system and can react to them in real time. The demonstration of the framework on smart agricultural systems, where agents manage irrigation and pest control tasks autonomously on a preliminary basis, was highly encouraging in significant improvements of resource efficiency and yield productivity. The approach proposed here marries reinforcement learning, scenario simulation, and adaptive proactive mechanisms to rid most of the challenges facing the lately built reactive IoT framework. Hence, the agents imbued with generative reasoning can decide based not only on sensor data but rather also on predicted-and-anticipated outcomes, thus dealing with the changing scenarios with the appropriate strategy-making. The generative cognitive architecture shows utmost potential for transforming autonomous systems in agriculture, transportation, and energy sectors. Specific areas around multi-agent collaboration, secure deployment, and ethical issues regarding autonomous decisions in the future are elaborated in the presented study

Using Negotiation and Large Language Models in Human – To Software Agent Negotiations

2025-05-19

Rustam Vahidov , Réal A. Carbonneau , J. P. Verma

Large Language Models for Acting and Planning

2025-05-19

Multimodal AI: The future of integrated intelligence

2025-05-17

Poorani Subramanian

This article explores the transformative potential of multimodal artificial intelligence systems, which integrate diverse data types including text, images, video, and audio into unified computational models. By seamlessly combining multiple … This article explores the transformative potential of multimodal artificial intelligence systems, which integrate diverse data types including text, images, video, and audio into unified computational models. By seamlessly combining multiple sensory modalities, these advanced frameworks enable more nuanced perception, interpretation, and response capabilities that parallel human cognitive processes. The architectural foundations of multimodal AI, including cross-modal learning techniques, modular architectures, and representation learning strategies, establish robust platforms for sophisticated data integration. Technological breakthroughs such as contrastive learning, dilated attention mechanisms, and multimodal transformers have addressed critical efficiency and performance barriers. The impact of these innovations extends across healthcare, autonomous systems, creative industries, and education, enabling unprecedented applications from disease progression prediction to enhanced artistic expression. As multimodal AI continues to mature, it promises to redefine the boundaries of human-computer interaction and establish new paradigms for artificial intelligence that more holistically engage with complex real-world environments.

Structural Results for Markov Decision Processes

2025-05-16

From DataOps to AIOps: How autonomous agents are revolutionizing data engineering

2025-05-15

Soumen Chakraborty

This comprehensive article examines the paradigm shift from traditional DataOps to AI-powered DataOps (AIOps), highlighting how autonomous agents are fundamentally transforming data engineering practices. The evolution represents not merely a … This comprehensive article examines the paradigm shift from traditional DataOps to AI-powered DataOps (AIOps), highlighting how autonomous agents are fundamentally transforming data engineering practices. The evolution represents not merely a technological upgrade but a complete reimagining of data pipeline management—moving from human-centered operations to self-learning, autonomous systems. The article explores the core pillars of AIOps: automated observability that contextually understands metrics beyond simple collection, predictive issue resolution that anticipates and prevents problems before they impact operations, and AI-driven metadata management that creates comprehensive knowledge graphs. It introduces the agentic framework comprising horizontal agents (resource optimization, performance monitoring, cost management, and security) and vertical agents (data quality, governance, domain-specific, and lineage tracking) that collaborate to create a truly intelligent ecosystem. The article further examines self-healing pipelines and emerging trends, including LLM-powered conversational interfaces, self-optimizing pipelines, and generative AI for documentation, while providing a phased implementation roadmap for organizations beginning their AIOps journey.

One Concept of Argument

2025-05-14

Marcin Lewiński