Deliberation scheduling for problem solving in time-constrained environments

Boddy, Mark S.; Dean, Thomas

doi:10.1016/0004-3702(94)90054-x

Cited by 191 publications

(111 citation statements)

References 5 publications

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“…Of course, in reality, this improvement is not so perfectly predictable, but these functions are often used as a modeling simplification. They are called (deterministic) performance profiles (Horvitz 1987;Boddy and Dean 1994;Zilberstein and Russell 1996).…”

Section: Variants Of the Metareasoning Problem And Their Complexitymentioning

confidence: 99%

Metareasoning as a Formal Computational Problem

Conitzer¹

2011

Metareasoning

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Metareasoning research often lays out high-level principles, which are then applied in the context of larger systems. While this approach has proven quite successful, it sometimes obscures how metareasoning can be seen as a crisp computational problem in its own right. This alternative view allows us to apply tools from the theory of algorithms and computational complexity to metareasoning. In this paper, we consider some known results on how variants of the metareasoning problem can be precisely formalized as computational problems, and shown to be computationally hard to solve to optimality. We discuss a variety of techniques for addressing these hardness results.

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Section: Variants Of the Metareasoning Problem And Their Complexitymentioning

confidence: 99%

Metareasoning as a Formal Computational Problem

Conitzer¹

2011

Metareasoning

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“…This formalisation results in a deliberation schedule procedure DS, that is described below. An important assumption Boddy and Dean make is that at any moment in time the agent knows about Boddy & Dean, 1994). Assume that an agent has two future events, c 1 and c 2 , to respond to, and aims to maximise the value of both responses.…”

Section: Continuous Deliberation Schedulingmentioning

confidence: 99%

“…it generates {␦ i } which maximises ⌺ n i i (␦ i ). For the detailed formulation of DS and the optimality proof, we refer the reader to Boddy & Dean (1994).…”

Section: Continuous Deliberation Schedulingmentioning

confidence: 99%

“…Boddy and Dean (1994) describe an extension of DS, which assumes there is only uncertain information about the times of occurrence of events. This procedure is called DS Ј.…”

Section: Continuous Deliberation Schedulingmentioning

confidence: 99%

“…It continually selects an amount of time, selects the algorithm to allocate this time to, and adds the selected time to the execution time for the selected algorithm. The methods of selection are explained in detail above and in Boddy & Dean (1994). Basically, the time between c 1 and c 2 is allocated to the path-planning algorithm, since no tour improvement can be done after c 1 .…”

Section: Continuous Deliberation Schedulingmentioning

confidence: 99%

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The control of reasoning in resource-bounded agents

Schut¹,

Wooldridge²

2001

The Knowledge Engineering Review

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Autonomous agents are systems capable of autonomous decision-making in real-time environments. Computation is a valuable resource for such decision-making, and yet the amount of computation that an autonomous agent may carry out will be limited. It follows that an agent must be equipped with a mechanism that enables it to make the best possible use of the computational resources at its disposal. In this paper we review three approaches to the control of computation in resource-bounded agents. In addition to a detailed description of each framework, this paper compares and contrasts the approaches, and lists the advantages and disadvantages of each.

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Planning

Hertzberg¹

1999

Wiley Encyclopedia of Electrical and Electronics Engineering

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Deliberation scheduling for problem solving in time-constrained environments

Cited by 191 publications

References 5 publications

Metareasoning as a Formal Computational Problem

Metareasoning as a Formal Computational Problem

The control of reasoning in resource-bounded agents

Planning

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