The possibility that the agents the authors make are a little unclear.

We study the process of multi-agent reinforcement learning in the context ofload balancing in a distributed system, without use of either centralcoordination or explicit communication. We first define a precise frameworkin which to study adaptive load balancing, important features of which are itsstochastic nature and the purely local information available to individualagents. Given this framework, we show illuminating results on the interplaybetween basic adaptive behavior parameters and their effect on systemefficiency. We then investigate the properties of adaptive load balancing inheterogeneous populations, and address the issue of exploration vs.exploitation in that context. Finally, we show that naive use ofcommunication may not improve, and might even harm system efficiency.

Interactive simulation environments constitute one of today's promising emerging technologies, with applications in areas such as education, manufacturing, entertainment, and training. These environments are also rich domains for building and investigating intelligent automated agents, with requirements for the integration of a variety of agent capabilities but without the costs and demands of low-level perceptual processing or robotic control. Our current target is intelligent automated pilots for battlefield-simulation environments. This article provides an overview of this domain and project by analyzing the challenges that automated pilots face in battlefield simulations, describing how TacAir-Soar is successfully able to address many of them -- TacAir-Soar pilots have already successfully participated in constrained air-combat simulations against expert human pilots -- and discussing the issues involved in resolving the remaining research challenges.

The Association for the Advancement of Artificial Intelligence held its 1994 Fall Symposium Series on November 4-6 at the Monteleone Hotel in New Orleans, Louisiana. This article contains summaries of the five symposia that were conducted: (1) Control of the Physical World by Intelligent Agents, (2) Improving Instruction of Introductory AI, (3) Knowledge Representation for Natural Language Processing in Implemented Systems, (4) Planning and Learning: On to Real Applications, and (5) Relevance.

Interactive simulation environments constitute one of today's promising emerging technologies, with applications in areas such as education, manufacturing, entertainment, and training. These environments are also rich domains for building and investigating intelligent automated agents, with requirements for the integration of a variety of agent capabilities but without the costs and demands of low-level perceptual processing or robotic control. Our project is aimed at developing humanlike, intelligent agents that can interact with each other, as well as with humans, in such virtual environments. Our current target is intelligent automated pilots for battlefield-simulation environments. These dynamic, interactive, multiagent environments pose interesting challenges for research on specialized agent capabilities as well as on the integration of these capabilities in the development of "complete" pilot agents. We are addressing these challenges through development of a pilot agent, called TacAir-Soar, within the Soar architecture. This article provides an overview of this domain and project by analyzing the challenges that automated pilots face in battlefield simulations, describing how TacAir-Soar is successfully able to address many of them -- TacAir-Soar pilots have already successfully participated in constrained air-combat simulations against expert human pilots -- and discussing the issues involved in resolving the remaining research challenges.

Fall 1994, 63-75 Abbott, Kathy, see Orlando, Nancy AI and NP-Hard Problems: 1993 Spring Alterman, Richard, see Hendler, James Abhyankar, R. B. Review of Computing Symposium Report.

The Association for the Advancement of Artificial Intelligence (AAAI) held its 1994 Spring Symposium Series on 19-23 March at Stanford University, Stanford, California. This article contains summaries of 10 of the 11 symposia that were conducted: Applications of Computer Vision in Medical Image Processing; AI in Medicine: Interpreting Clinical Data; Believable Agents; Computational Organization Design; Decision-Theoretic Planning; Detecting and Resolving Errors in Manufacturing Systems; Goal-Driven Learning; Intelligent Multimedia, Multimodal Systems; Software Agents; and Toward Physical Interaction and Manipulation. Papers of most of the symposia are available as technical reports from AAAI.

The Association for the Advancement of Artificial Intelligence (AAAI) held its 1994 Spring Symposium Series on 19-23 March at Stanford University, Stanford, California. This article contains summaries of 10 of the 11 symposia that were conducted: Applications of Computer Vision in Medical Image Processing; AI in Medicine: Interpreting Clinical Data; Believable Agents; Computational Organization Design; Decision-Theoretic Planning; Detecting and Resolving Errors in Manufacturing Systems; Goal-Driven Learning; Intelligent Multimedia, Multimodal Systems; Software Agents; and Toward Physical Interaction and Manipulation. Papers of most of the symposia are available as technical reports from AAAI.

These software between telephone, television, agents are on their way, and they're going to The be getting a lot of things accomplished by basic idea is that the networks that constitute interacting with each other. The question is, our telephone infrastructure, our television How will these agents be cooperating with (particularly cable) infrastructure, and our each other, competing with each other, and computer infrastructure will be coalescing into negotiating with each other? Now, the agents that we are interested in Another example is routing among looking at are heterogeneous, self-motivated telecommunication networks. The systems are not assumed to be packets, can pass over a network controlled by centrally designed. For example, if you have a one company onto another network controlled personal digital assistant, you might have one by another company, or it can pass that was built by IBM, but the next person through one country on through another. Computers that control a telecommunications They don't necessarily have a notion of global network might find it beneficial to enter into utility. Each personal digital assistant or agreements with other computers that control each agent operating from your machine is other networks about routing packets more interested in what your idea of utility is and efficiently from source to destination. The in how to further your notion of goodness. We're other agents ask them to do unless they have Another example is the proliferation of shared databases, where there's information They have sprung up with a vengeance in the last decade.

The Association for the Advancement of Artificial Intelligence held its 1993 Fall Symposium Series on October 22-24 in Raleigh, North Carolina. This article contains summaries of the six symposia that were conducted: Automated Deduction in Nonstandard Logics; Games: Planning and Learning; Human-Computer Collaboration: Reconciling Theory, Synthesizing Practice; Instantiating Intelligent Agents; and Machine Learning and Computer Vision: What, Why, and How?