An interval-based temporal logic is introduced, together with a computationally effective reasoning algorithm based on constraint propagation. This system is notable in offering a delicate balance between

Maintaining knowledge about temporal intervals

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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 properties 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.

/pdf/intelligent-agents-theory-and-practice-5dchj7p8pc.pdf

Intelligent Agents: Theory and Practice

The contract net protocol has been developed to specify problem-solving communication and control for nodes in a distributed problem solver. Task distribution is affected by a negotiation process, a discussion carried on between nodes with tasks to be executed and nodes that may be able to execute those tasks.

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The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver

http://www-anw.cs.umass.edu/~barto/courses/cs687/Sutton-Precup-Singh-AIJ99.pdf

Between MDPs and semi-MDPs: a framework for temporal abstraction in reinforcement learning

: This report describes progress to date in the ability of a computer system to understand and reason about actions. A new method of representing actions within a computer's memory has been developed, and this new representation, called the "procedural net," has been employed in developing new strategies for solving problems and monitoring the execution of the resulting solutions. A set of running computer programs, called the NOAH (Nets Of Action Hierarchies) system, embodies this representation. Its major goal is to provide a framework for storing expertise about the actions of a particular task domain, and to impart that expertise to a human in the cooperative achievement of nontrivial tasks. A problem is presented to NOAH as a statement that is to be made true by applying a sequence of actions in an initial state of the world. The actions are drawn from a set of actions previously defined to the system. NOAH first creates a one-step solution to the problem, then it progressively expands the level of detail of the solution, filling in ever more detailed actions. All the individual actions, composed into plans at differing levels of detail, are stored in the procedural net. The system avoids imposing unnecessary constraints on the order of the actions in a plan. Thus, plans are represented as partial orderings of actions, rather than as linear sequences. The same data structure is used to guide the human user through a task. Since the system has planned the task at varying levels of detail, it can issue requests for action to the user at varying levels of detail, depending on his/her competence and understanding of the higher level actions. If more detail is needed than was originally planned for, or if an unexpected event causes the plan to go awry, the system can continue to plan from any point during execution. In essence, the structure of a plan of actions is as important for problem solving and execution monitoring as the nature of the actions themselves.

/pdf/a-structure-for-plans-and-behavior-5g7anp5vvf.pdf

A Structure for Plans and Behavior

Planning in a hierarchy of abstraction spaces

A user of an interactive medium may select advertising for display on the user's avatar, property, or other user-associated environment. The invention presents one or more advertisements to the user and allows the user to select at least one advertisement to display. The user may also choose a location for displaying the selected advertisement. The invention presents the selected advertisement to other users of the interactive medium. The invention tracks these presentations or displays and rewards the original user based on the presentation. The tracking data may also be used to bill the advertiser or optimize the process of selecting and displaying advertisements.

System and method for consumer-selected advertising and branding in interactive media

Aspects of an intelligent interface that provides natural language access to a large body of data distributed over a computer network are described. The overall system architecture is presented, showing how a user is buffered from the actual database management systems (DBMSs) by three layers of insulating components. These layers operate in series to convert natural language queries into calls to DBMSs at remote sites. Attention is then focused on the first of the insulating components, the natural language system. A pragmatic approach to language access that has proved useful for building interfaces to databases is described and illustrated by examples. Special language features that increase system usability, such as spelling correction, processing of incomplete inputs, and run-time system personalization, are also discussed. The language system is contrasted with other work in applied natural language processing, and the system's limitations are analyzed.

Developing a natural language interface to complex data

We usually think of plans as linear sequences of actions. This is because plans are usually executed one step at a time. But plans themselves are not constrained by limitations of linearity. This paper describes a new information structure, called the procedural net, that represents a plan as a partial ordering of actions with respec to time. By avoiding premature commitments to a particular order for achieving subgoals, a problem-solving system using this representation can deal easily and directly with problems that are otherwise very difficult to solve.

/pdf/the-nonlinear-nature-of-plans-y5hn5na1be.pdf

Earl D. Sacerdoti

Papers

A Structure for Plans and Behavior

Planning in a hierarchy of abstraction spaces

System and method for consumer-selected advertising and branding in interactive media

Developing a natural language interface to complex data

The nonlinear nature of plans