Results 1 - 10
of
139
Intelligent agents: Theory and practice
- The Knowledge Engineering Review
, 1995
"... The concept of an agent has become important in both Artificial Intelligence (AI) 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 age ..."
Abstract
-
Cited by 1441 (85 self)
- Add to MetaCart
(Show Context)
The concept of an agent has become important in both Artificial Intelligence (AI) 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 prop-erties 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.
BDI Agents: From Theory to Practice
- IN PROCEEDINGS OF THE FIRST INTERNATIONAL CONFERENCE ON MULTI-AGENT SYSTEMS (ICMAS-95
, 1995
"... The study of computational agents capable of rational behaviour has received a great deal of attention in recent years. Theoretical formalizations of such agents and their implementations have proceeded in parallel with little or no connection between them. This paper explores a particular typ ..."
Abstract
-
Cited by 892 (3 self)
- Add to MetaCart
The study of computational agents capable of rational behaviour has received a great deal of attention in recent years. Theoretical formalizations of such agents and their implementations have proceeded in parallel with little or no connection between them. This paper explores a particular type of rational agent, a BeliefDesire -Intention (BDI) agent. The primary aim of this paper is to integrate (a) the theoretical foundations of BDI agents from both a quantitative decision-theoretic perspective and a symbolic reasoning perspective; (b) the implementations of BDI agents from an ideal theoretical perspective and a more practical perspective; and (c) the building of large-scale applications based on BDI agents. In particular, an air-traffic management application will be described from both a theoretical and an implementation perspective.
GOLOG: A Logic Programming Language for Dynamic Domains
, 1994
"... This paper proposes a new logic programming language called GOLOG whose interpreter automatically maintains an explicit representation of the dynamic world being modeled, on the basis of user supplied axioms about the preconditions and effects of actions and the initial state of the world. This allo ..."
Abstract
-
Cited by 628 (74 self)
- Add to MetaCart
(Show Context)
This paper proposes a new logic programming language called GOLOG whose interpreter automatically maintains an explicit representation of the dynamic world being modeled, on the basis of user supplied axioms about the preconditions and effects of actions and the initial state of the world. This allows programs to reason about the state of the world and consider the effects of various possible courses of action before committing to a particular behavior. The net effect is that programs may be written at a much higher level of abstraction than is usually possible. The language appears well suited for applications in high level control of robots and industrial processes, intelligent software agents, discrete event simulation, etc. It is based on a formal theory of action specified in an extended version of the situation calculus. A prototype implementation in Prolog has been developed.
Knowledge and Common Knowledge in a Distributed Environment
- Journal of the ACM
, 1984
"... : Reasoning about knowledge seems to play a fundamental role in distributed systems. Indeed, such reasoning is a central part of the informal intuitive arguments used in the design of distributed protocols. Communication in a distributed system can be viewed as the act of transforming the system&apo ..."
Abstract
-
Cited by 578 (55 self)
- Add to MetaCart
: Reasoning about knowledge seems to play a fundamental role in distributed systems. Indeed, such reasoning is a central part of the informal intuitive arguments used in the design of distributed protocols. Communication in a distributed system can be viewed as the act of transforming the system's state of knowledge. This paper presents a general framework for formalizing and reasoning about knowledge in distributed systems. We argue that states of knowledge of groups of processors are useful concepts for the design and analysis of distributed protocols. In particular, distributed knowledge corresponds to knowledge that is "distributed" among the members of the group, while common knowledge corresponds to a fact being "publicly known". The relationship between common knowledge and a variety of desirable actions in a distributed system is illustrated. Furthermore, it is shown that, formally speaking, in practical systems common knowledge cannot be attained. A number of weaker variants...
Controlling Cooperative Problem Solving in Industrial Multi-Agent Systems using Joint Intentions
- ARTIFICIAL INTELLIGENCE JOURNAL
, 1995
"... One reason why Distributed AI (DAI) technology has been deployed in relatively few real-size applications is that it lacks a clear and implementable model of cooperative problem solving which specifies how agents should operate and interact in complex, dynamic and unpredictable environments. As a co ..."
Abstract
-
Cited by 331 (36 self)
- Add to MetaCart
One reason why Distributed AI (DAI) technology has been deployed in relatively few real-size applications is that it lacks a clear and implementable model of cooperative problem solving which specifies how agents should operate and interact in complex, dynamic and unpredictable environments. As a consequence of the experience gained whilst building a number of DAI systems for industrial applications, a new principled model of cooperation has been developed. This model, called Joint Responsibility, has the notion of joint intentions at its core. It specifies pre-conditions which must be attained before collaboration can commence and prescribes how individuals should behave both when joint activity is progressing satisfactorily and also when it runs into difficulty. The theoretical model has been used to guide the implementation of a general-purpose cooperation framework and the qualitative and quantitative benefits of this implementation have been assessed through a series of comparativ...
Agent theories, architectures, and languages: a survey
, 1995
"... The concept of an agent has recently become important in Artificial Intelligence (AI), and its relatively youthful subfield, Distributed AI (DAI). 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 ..."
Abstract
-
Cited by 321 (2 self)
- Add to MetaCart
(Show Context)
The concept of an agent has recently become important in Artificial Intelligence (AI), and its relatively youthful subfield, Distributed AI (DAI). 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 the area into three themes (though as the reader will see, these 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 constructing 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 typically 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 key issues, and point to work that elaborates on them. The paper closes with a detailed bibliography, and some bibliographical remarks. 1
How To Do the Right Thing
- Connection Science Journal
, 1989
"... This paper presents a novel approach to the problem of action selection for an autonomous agent. An agent is viewed as a collection of com- petence modules. Action selection is modeled as an emergent property of an activation/inhibition dynamics among these modules. A con- crete action selection ..."
Abstract
-
Cited by 269 (0 self)
- Add to MetaCart
This paper presents a novel approach to the problem of action selection for an autonomous agent. An agent is viewed as a collection of com- petence modules. Action selection is modeled as an emergent property of an activation/inhibition dynamics among these modules. A con- crete action selection algorithm is presented and a detailed account of the results is given. This algorithm combines characteristics of both traditional planners and reactive systems: it produces fast and robust activity in a tight interaction loop with the environment, while at the same time allowing for some prediction and planning to take place. It provides global parameters, which one can use to tune the action selection behavior to the characteristics of the task environment. As such one can smoothly trade off goal-orientedness for situation-orientedness, bias towards ongoing plans (inertia) for adaptivity, thoughtfulness for speed, and adjust its sensitivity to goal conflicts.
Agent-Oriented Software Engineering
, 1999
"... Software and knowledge... In this article, we argue that intelligent agents and agent-based systems offer novel opportunities for developing effective tools and techniques. Following a discussion on the classic subject of what makes software complex, we introduce intelligent agents as software struc ..."
Abstract
-
Cited by 259 (19 self)
- Add to MetaCart
(Show Context)
Software and knowledge... In this article, we argue that intelligent agents and agent-based systems offer novel opportunities for developing effective tools and techniques. Following a discussion on the classic subject of what makes software complex, we introduce intelligent agents as software structures capable of making "rational decisions". Such rational decision-makers are well-suited to the construction of certain types of software, which mainstream software engineering has had little success with. We then go on to examine a number of prototype techniques proposed for engineering agent systems, including formal specification and verification methods for agent systems, and techniques for implementing agent specifications
Learning to coordinate behaviors
- In Proceedings of AAAI-90
, 1990
"... We describe an algorithm which allows a behavior-based robot to learn on the basis of positive and negative feedback when to activate its behaviors. In accordance with the philosophy of behavior-based robots, the algorithm is completely distributed: each of the behaviors independently tries to find ..."
Abstract
-
Cited by 229 (3 self)
- Add to MetaCart
(Show Context)
We describe an algorithm which allows a behavior-based robot to learn on the basis of positive and negative feedback when to activate its behaviors. In accordance with the philosophy of behavior-based robots, the algorithm is completely distributed: each of the behaviors independently tries to find out (i) whether it is relevant (ie. whether it is at all correlated to positive feedback) and (ii) what the conditions are under which it becomes reliable (i.e. the conditions under which it maximizes the probability of receiving positive feedback and minimizes the probability of receiving negative feedback). The algorithm has been tested successfully on an autonomous 6-legged robot which had to learn how to coordinate its legs so as to walk forward. Situation of the Problem Since 1985, the MIT Mobile Robot group has advocated a radically different architecture for autonomous intelligent agents (Brooks, 1986). Instead of decomposing the architecture into functional modules, such as perception, modeling, and planning (figure 1), the architecture is decomposed into task-achieving modules, also called behaviors (figure 2). This novel approach has already demonstrated to be very successful and similar approaches have become more
