Mobile Agents and the Future of the Internet
2/18/00 664 - Mobile Agents and the Future of the Internet , David Kotz and Bob Gray, ACM Operating Systems Review, 33(3), Aug 1999, pp 7-13.,-- an update of aposition paper that appeared at the Workshop Mobile Agents in the Context of Competition and Cooperation (MAC3) at Autonomous Agents, May1, 1999, in Seattle, Washington, USA.
Game Theory: An Introductory Sketch
1/23/00 54 - Roger A. McCain (Drexel University, Philadelphia, Pennsylvania)maintains a web site titled "Game Theory: An Introductory Sketch" which provides a readable elementaryexposition of basic game theory principles for non-specialists.
MITECS: Theory of Mind
1/2/00 18 - "Understanding other people is one of the most fundamentalhuman problems. We know much less, however, about ourability to understand other minds than about our ability tounderstand the physical world. The branch of cognitive sciencethat concerns our understanding of the minds of ourselves andothers has come to be called "theory of mind," though it shouldperhaps be called " theory of theory of mind." It involvespsychological theorizing about our ordinary, intuitive, "folk"understanding of the mind. ..." -- Alison Gopnik
MITECS: Knowledge Representation
1/2/00 19 - "Knowledge representation (KR) refers to the general topic ofhow information can be appropriately encoded and utilized incomputational models of cognition. ..." -- Patrick Hayes
MITECS: Machine Learning
1/2/00 18 - "The goal of machine learning is to build computer systems thatcan adapt and learn from their experience. Different learningtechniques have been developed for different performancetasks. The primary tasks that have been investigated areSUPERVISED LEARNING for discrete decision-making,supervised learning for continuous prediction,REINFORCEMENT LEARNING for sequential decisionmaking, and UNSUPERVISED LEARNING. ..." -- Tom Dietterich
MITECS: Reinforcement Learning
1/2/00 16 - "Reinforcement learning is an approach to artificial intelligencethat emphasizes learning by the individual from its interactionwith its environment. This contrasts with classical approachesto artificial intelligence and MACHINE LEARNING, which havedownplayed learning from interaction, focusing instead onlearning from a knowledgeable teacher, or on reasoning from acomplete model of the environment. ..." -- Richard S. Sutton
MITECS: Unsupervised Learning
1/2/00 14 - "Unsupervised learning studies how systems can learn torepresent particular input patterns in a way that reflects thestatistical structure of the overall collection of input patterns. Bycontrast with SUPERVISED LEARNING orREINFORCEMENT LEARNING, there are no explicit targetoutputs or environmental evaluations associated with eachinput; rather, the unsupervised learner brings to bear priorbiases as to what aspects of the structure of the input shouldbe captured in the output. ..." -- Peter Dayan
MITECS: Self-Organizing Systems
1/2/00 15 - "Self-organization refers to spontaneous ordering tendenciessometimes observed in certain classes of complex systems,both artificial and natural. ..." -- David Depew and Bruce Weber
MITECS: Artificial Life
1/2/00 14 - "Artificial life (A-Life) uses informational concepts and computermodeling to study life in general, and terrestrial life in particular.It aims to explain particular vital phenomena, ranging from theorigin of biochemical metabolisms to the coevolution ofbehavioral strategies, and also the abstract properties of lifeas such ("life as it could be"). ..." -- Margaret A. Boden
1/2/00 14 - "Metareasoning is reasoning about reasoning -- in its broadestsense, any computational process concerned with theoperation of some other computational process within thesame entity...." -- Stuart J. Russell
MITECS: Propositional Attitudes
1/2/00 13 - "Propositional attitudes are mental states with representationalcontent. Belief is the most prominent example of apropositional attitude. Others include intention, wishing andwanting, hope and fear, seeming and appearing, and tacitpresupposition. ..." -- Robert Stalnaker
MITECS: Intentional Stance
1/2/00 12 - "The intentional stance is the strategy of interpreting thebehavior of an entity (person, animal, artifact, or the like) bytreating it as if it were a rational agent that governed its"choice" of "action" by a "consideration" of its "beliefs" and"desires." ..." -- Daniel Dennett
MITECS: Multiagent Systems
1/2/00 37 - Multiagent systems are distributed computer systems in which the designersascribe to component modules autonomy, mental state, and othercharacteristics of agency. -- -- Michael P. Wellman
MITECS: Intelligent Agent Architecture
1/2/00 33 - Intelligent agent architecture is a model of an intelligent information-processingsystem defining its major subsystems, their functional roles, and the flow ofinformation and control among them. -- Stanley J. Rosenschein
MITECS: Rational Agency
1/2/00 14 - "In philosophy of mind, rationality is conceived of as a coherence requirement onpersonal identity: roughly, "No rationality, no agent." The agent must have ameans-ends competence to fit its actions or decisions, according to its beliefsor knowledge-representation, to its desires or goal-structure....", Christopher Cherniak, MITECS
12/8/99 18 - a special web site provided by the AmericanAssociation for Artificial Intelligence (AAAI) for students,teachers, journalists, and everyone who would like to learnmore about what artificial intelligence is, and what AIscientists do.
Agents working together
1/21/00 17 - A short article by Don Barker written for PC AI on agent communication and cooperation.
Artificial Life (tutorial)
2/10/00 22 - Ray, T S, In press, Artificial Life, In: ``From Atoms to Mind'', Gilbert, Walter, and GlaucoTocchini Valentini, [eds]. Istituto della Enciclopedia Italiana Treccani. Rome.