Results 1 - 10 of 11,251

The Role of Emotion in Believable Agents

by Joseph Bates - Communications of the ACM , 1994
"... Articial intelligence researchers attempting to create engaging apparently living creatures may nd important insight in the work of artists who have explored the idea of believable character In particular appropriately timed and clearly expressed emotion is a central requirement for believable ch ..."
Abstract - Cited by 557 (1 self) - Add to MetaCart
characters We discuss these ideas and suggest how they may apply to believable interactive characters which we call believable agents This work was supported in part by Fujitsu Laboratories and Mitsubishi Electric Research Laborato ries The views and conclusions contained in this document are those

BDI Agents: From Theory to Practice

by Anand S. Rao, Michael P. Georgeff - 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
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

Markov games as a framework for multi-agent reinforcement learning

by Michael L. Littman - IN PROCEEDINGS OF THE ELEVENTH INTERNATIONAL CONFERENCE ON MACHINE LEARNING , 1994
"... In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function. In this solipsistic view, secondary agents can only be part of the environment and are therefore fixed in their behavior ..."
Abstract - Cited by 601 (13 self) - Add to MetaCart
In the Markov decision process (MDP) formalization of reinforcement learning, a single adaptive agent interacts with an environment defined by a probabilistic transition function. In this solipsistic view, secondary agents can only be part of the environment and are therefore fixed

Separation of ownership and control

by Eugene F. Fama, Michael C. Jensen - JOURNAL OF LAW AND ECONOMICS , 1983
"... This paper analyzes the survival of organizations in which decision agents do not bear a major share of the wealth effects of their decisions. This is what the literature on large corporations calls separation of “ownership” and “control.” Such separation of decision and risk bearing functio ..."
Abstract - Cited by 1661 (8 self) - Add to MetaCart
This paper analyzes the survival of organizations in which decision agents do not bear a major share of the wealth effects of their decisions. This is what the literature on large corporations calls separation of “ownership” and “control.” Such separation of decision and risk bearing

Redesigning the agents’ decision machinery

by Luis Antunes, Helder Coelho - of Lecture Notes in Artiflcial Intelligence. Springer-Verlag, 2000. Revised and extended version of the paper presented in the Workshop on Afiect in Interactions (Towards , 1999
"... Abstract. In a multi-agent system, agents must decide what to do and by what order. Autonomy is a key notion in such a system, since it is mainly the autonomy of the agents that makes the environment unpredictable and complex. From a user standpoint, autonomy is equally important as an ingredient th ..."
Abstract - Cited by 3 (3 self) - Add to MetaCart
in choosing which of the agent’s goals are going to be addressed next. We have proposed the BVG (Beliefs, Values, Goals) architecture with the idea of making decisions using multiple evaluations of a situation, taking the notion of value as central in the motivational mechanisms in the agent’s mind. The agent

Formalising trust as a computational concept

by Stephen Paul Marsh , 1994
"... Trust is a judgement of unquestionable utility — as humans we use it every day of our lives. However, trust has suffered from an imperfect understanding, a plethora of definitions, and informal use in the literature and in everyday life. It is common to say “I trust you, ” but what does that mean? T ..."
Abstract - Cited by 529 (6 self) - Add to MetaCart
? This thesis provides a clarification of trust. We present a formalism for trust which provides us with a tool for precise discussion. The formalism is implementable: it can be embedded in an artificial agent, enabling the agent to make trust-based decisions. Its applicability in the domain of Distributed

Formal and real authority in organizations

by Jean Tirole - The Journal of Political Economy , 1997
"... This paper develops a theory of the allocation of formal authority (the right to decide) and real authority (the effective control over decisions) within organizations, and it illustrates how a formally integrated structure can accommodate various degrees of "real" integration. Real author ..."
Abstract - Cited by 856 (24 self) - Add to MetaCart
This paper develops a theory of the allocation of formal authority (the right to decide) and real authority (the effective control over decisions) within organizations, and it illustrates how a formally integrated structure can accommodate various degrees of "real" integration. Real

Towards flexible teamwork

by Milind Tambe - JOURNAL OF ARTIFICIAL INTELLIGENCE RESEARCH , 1997
"... 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 obst ..."
Abstract - Cited by 570 (59 self) - Add to MetaCart
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

Reinforcement learning: a survey

by Leslie Pack Kaelbling, Michael L. Littman, Andrew W. Moore - Journal of Artificial Intelligence Research , 1996
"... This paper surveys the field of reinforcement learning from a computer-science perspective. It is written to be accessible to researchers familiar with machine learning. Both the historical basis of the field and a broad selection of current work are summarized. Reinforcement learning is the problem ..."
Abstract - Cited by 1714 (25 self) - Add to MetaCart
is the problem faced by an agent that learns behavior through trial-and-error interactions with a dynamic environment. The work described here has a resemblance to work in psychology, but differs considerably in the details and in the use of the word "reinforcement." The paper discusses central issues

Negotiation decision functions for autonomous agents

by Peyman Faratin, Carles Sierra, Nick R. Jennings - International Journal of Robotics and Autonomous Systems , 1998
"... We present a formal model of negotiation between autonomous agents. The purpose of the negotiation is to reach an agreement about the provision of a service by one agent for another. The model de nes a range of strategies and tactics that agents can employ to generate initial o ers, evaluate proposa ..."
Abstract - Cited by 359 (58 self) - Add to MetaCart
We present a formal model of negotiation between autonomous agents. The purpose of the negotiation is to reach an agreement about the provision of a service by one agent for another. The model de nes a range of strategies and tactics that agents can employ to generate initial o ers, evaluate
Results 1 - 10 of 11,251