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Comparative Analysis of Frameworks for Knowledge-Intensive Intelligent Agents

AI Magazine

A recurring requirement for human-level artificial intelligence is the incorporation of vast amounts of knowledge into a software agent that can use the knowledge in an efficient and organized fashion. This article discusses representations and processes for agents and behavior models that integrate large, diverse knowledge stores, are long-lived, and exhibit high degrees of competence and flexibility while interacting with complex environments. There are many different approaches to building such agents, and understanding the important commonalities and differences between approaches is often difficult. We introduce a new approach to comparing frameworks based on the notions of commitment, reconsideration, and a categorization of representations and processes. We review four agent frameworks, concentrating on the major representations and processes each directly supports. By organizing the approaches according to a common nomenclature, the analysis highlights points of similarity and difference and suggests directions for integrating and unifying disparate approaches and for incorporating research results from one framework into alternatives.


Toward Virtual Humans

AI Magazine

This article describes the virtual humans developed as part of the Mission Rehearsal Exercise project, a virtual reality-based training system. This project is an ambitious exercise in integration, both in the sense of integrating technology with entertainment industry content, but also in that we have joined a number of component technologies that have not been integrated before. This integration has not only raised new research issues, but it has also suggested some new approaches to difficult problems. We describe the key capabilities of the virtual humans, including task representation and reasoning, natural language dialogue, and emotion reasoning, and show how these capabilities are integrated to provide more human-level intelligence than would otherwise be possible.


Cognitive Architectures and General Intelligent Systems

AI Magazine

In this article, I claim that research on cognitive architectures is an important path to the development of general intelligent systems. I contrast this paradigm with other approaches to constructing such systems, and I review the theoretical commitments associated with a cognitive architecture. I illustrate these ideas using a particular architecture -- ICARUS -- by examining its claims about memories, about the representation and organization of knowledge, and about the performance and learning mechanisms that affect memory structures. I also consider the high-level programming language that embodies these commitments, drawing examples from the domain of in-city driving. In closing, I consider ICARUS's relation to other cognitive architectures and discuss some open issues that deserve increased attention.


Asynchronous Partial Overlay: A New Algorithm for Solving Distributed Constraint Satisfaction Problems

Journal of Artificial Intelligence Research

Distributed Constraint Satisfaction (DCSP) has long been considered an important problem in multi-agent systems research. This is because many real-world problems can be represented as constraint satisfaction and these problems often present themselves in a distributed form. In this article, we present a new complete, distributed algorithm called asynchronous partial overlay (APO) for solving DCSPs that is based on a cooperative mediation process. The primary ideas behind this algorithm are that agents, when acting as a mediator, centralize small, relevant portions of the DCSP, that these centralized subproblems overlap, and that agents increase the size of their subproblems along critical paths within the DCSP as the problem solving unfolds. We present empirical evidence that shows that APO outperforms other known, complete DCSP techniques.


A Continuation Method for Nash Equilibria in Structured Games

Journal of Artificial Intelligence Research

Structured game representations have recently attracted interest as models for multi-agent artificial intelligence scenarios, with rational behavior most commonly characterized by Nash equilibria. This paper presents efficient, exact algorithms for computing Nash equilibria in structured game representations, including both graphical games and multi-agent influence diagrams (MAIDs). The algorithms are derived from a continuation method for normal-form and extensive-form games due to Govindan and Wilson; they follow a trajectory through a space of perturbed games and their equilibria, exploiting game structure through fast computation of the Jacobian of the payoff function. They are theoretically guaranteed to find at least one equilibrium of the game, and may find more. Our approach provides the first efficient algorithm for computing exact equilibria in graphical games with arbitrary topology, and the first algorithm to exploit fine-grained structural properties of MAIDs. Experimental results are presented demonstrating the effectiveness of the algorithms and comparing them to predecessors. The running time of the graphical game algorithm is similar to, and often better than, the running time of previous approximate algorithms. The algorithm for MAIDs can effectively solve games that are much larger than those solvable by previous methods.


Representing Conversations for Scalable Overhearing

Journal of Artificial Intelligence Research

Open distributed multi-agent systems are gaining interest in the academic community and in industry. In such open settings, agents are often coordinated using standardized agent conversation protocols. The representation of such protocols (for analysis, validation, monitoring, etc) is an important aspect of multi-agent applications. Recently, Petri nets have been shown to be an interesting approach to such representation, and radically different approaches using Petri nets have been proposed. However, their relative strengths and weaknesses have not been examined. Moreover, their scalability and suitability for different tasks have not been addressed. This paper addresses both these challenges. First, we analyze existing Petri net representations in terms of their scalability and appropriateness for overhearing, an important task in monitoring open multi-agent systems. Then, building on the insights gained, we introduce a novel representation using Colored Petri nets that explicitly represent legal joint conversation states and messages. This representation approach offers significant improvements in scalability and is particularly suitable for overhearing. Furthermore, we show that this new representation offers a comprehensive coverage of all conversation features of FIPA conversation standards. We also present a procedure for transforming AUML conversation protocol diagrams (a standard human-readable representation), to our Colored Petri net representation.


Report on the Fourth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2005)

AI Magazine

The 2005 Autonomous Agents and Multiagent Systems Conference (AAMAS 2005) was held July 25-29, 2005, at the University of Utrecht, the Netherlands. This report reviews the activities of that conference, including the workshop and tutorial programs, the main conference and poster tracks, the industry paper track, the demonstration track and sponsor demonstration sessions, the invited talks, exhibition, doctoral mentoring program, as well the sponsorship and scholarships activities.


Negotiating Socially Optimal Allocations of Resources

Journal of Artificial Intelligence Research

A multiagent system may be thought of as an artificial society of autonomous software agents and we can apply concepts borrowed from welfare economics and social choice theory to assess the social welfare of such an agent society. In this paper, we study an abstract negotiation framework where agents can agree on multilateral deals to exchange bundles of indivisible resources. We then analyse how these deals affect social welfare for different instances of the basic framework and different interpretations of the concept of social welfare itself. In particular, we show how certain classes of deals are both sufficient and necessary to guarantee that a socially optimal allocation of resources will be reached eventually.


The Second International Conference on Informatics in Control, Automation, and Robotics

AI Magazine

These workshops, although quite specialized, have covered areas of great interest for the conference delegates, namely: "Multiagent System Robotics" (MARS), "Biosignal Processing and Classification" (BPC), and "Artificial Neural Networks and Intelligent Information Processing" (ANNIIP). In the program of this conference for publication in the proceedings were included oral presentations (full and for presentation at the conference; papers and short papers) and posters, of these, 166 papers were organized in three simultaneous selected for oral presentation (67 full tracks: "Intelligent Control Systems papers and 99 short papers) and 63 papers and Optimization," "Robotics and Automation," were accepted for poster presentation. Furthermore, less than 60 percent, and the full paper (ICINCO 2005) was held in Barcelona ICINCO 2005 included acceptance ratio was 17 percent.


Components, Curriculum, and Community: Robots and Robotics in Undergraduate AI Education

AI Magazine

Although the Lego RCX's has helped guide Sony's own choice of Hitachi H8 microcontroller lists at 16 megahertz next-generation AIBO features and software and 32 kilobytes of memory, the overhead support. As for two-legged platforms, the University of the firmware and interpreter yield of Freiburg has already prototyped a about 10 kilobytes and 500 hertz throughput soccer team of Robosapiens running from for a typical user--slightly better with alternative handheld computers.