Doyle J. (1992) Rationality and its roles in reasoning, Computational Intelligence 8(2), pp. 376--409.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....Savage [77] who simultaneously axiomatized utility and subjective behavior) This is also in keeping with a large (and growing) body of work within artificial intelligence that attributes rationality (or explores the consequences of attributing rationality) to autonomous agents. See, for example, [46, 25, 70, 12, 42, 34]. 1.3 Overview of this Article In this article we present a method for reaching consensus based on the Clarke Tax mechanism [6, 7] CTm) and consider how this mechanism could be used among rational automated agents. Parts of this work have appeared previously in [18, 22, 20, 19] In Section ....

Jon Doyle. Rationality and its role in reasoning. Computational Intelligence, 8(2):376-- 409, May 1992.

....14, 19, 21, 22] 2 The problem of deliberation cost has been widely discussed in artificial intelligence, economics, engineering and philosophy. In artificial intelligence in particular, researchers have proposed a number of meta level architectures to control the cost of base level reasoning [4, 7, 9, 12, 18]. One promising approach is to use anytime [3] or flexible [10] algorithms, which allow the execution time to be specified, either as a parameter or by an interrupt, and exhibit a time quality tradeoff defined by a performance profile. They provide a simple means by which a system can control its ....

J. Doyle, Rationality and its roles in reasoning, In Proceedings of the Eighth National Conference on Artificial Intelligence, Boston, Massachusetts (1990) 1093--1100.

....cost [1, 4, 16, 21, 28, 31, 32] The problem of deliberation cost has been widely discussed in artificial intelligence, economics and philosophy. In artificial intelligence in particular, researchers have proposed a number of meta level architectures to control the cost of base level reasoning [5, 6, 8, 12, 16, 27]. One promising approach is to use anytime [7] orfiexible [14] algorithms, which allow the execution time to be specified, either as a parameter or by an interrupt, and exhibit a time quality tradeoff defined by a performance profile. They provide a simple means by which a system can control its ....

J. Doyle, Rationality and its roles in reasoning, In Proceedings of the Eighth National Conference on Artificial Intelligence, Boston, Massachusetts (1990) 1093-1 tOO.

....by whether information relevant to the task is distributed between the agents or primarily known by one agent [Walker and Whittaker, 1990; Guinn, 1993] 14 10 process. Desires: Agents may have different types of desires but here I assume that their only desire is to maximize utility[Doyle, 1992]. Intention Deliberation: decides which of a set of options to pursue (by an evaluation based on desires such as maximizing utility) Attention Working memory ( WM) the limited attention module constrains working memory and the retrieval of current beliefs and intentions that are used by ....

....shows, incoming messages about intentions and beliefs are subject to intention or belief deliberation. This provides the basis for abandoning the NO AUTONOMY ASSUMPTION while specifying why an agent would ac cept or reject another agent s proposal (see also [Galliers, 1989; Galliers, 1991b; Doyle, 1992] Agents evaluate assertions and proposals from other agents by assessing the support for assertions and the warrants for proposals. Finally, as figure 3 shows, this evaluation takes place under constraints of limited working memory, since the beliefs that can serve as supports or warrants must ....

[Article contains additional citation context not shown here]

Jon Doyle. Rationality and its roles in reasoning. Computational Intelligence, November 1992.

....the derived performance function to make predictions and to learn how to optimize agent dialogue behavior. In Section 5 we conclude and suggest future work. 2 PARADISE: A Framework for Deriving Performance Models for Dialogue PARADISE uses methods from decision theory [Keeney and Raiffa, 1976; Doyle, 1992] to combine a disparate set of performance measures (i.e. user satisfaction, task success, and dialogue cost, all of which have been previously noted in the literature) into a single performance evaluation function. The use of decision theory requires a specification of both the objectives of ....

Jon Doyle. Rationality and its roles in reasoning. Computational Intelligence, 8(2):376--409, 1992.

....deadlines. Ever since then, the concept of imprecise computation has been applied to solve several diverse problems [6, 7, 8, 9] The idea of anytime algorithms is also similar to the notion of rationality in automated reasoning and search investigated by Russel et al. in [10, 11] Doyle in [12] and D Ambrosio in [13] Real time computational tasks that are anytime algorithms, prove to be useful in the design of real time systems. The property of anytime algorithms to trade computational time for decision quality results in optimal performance of real time systems [14, 15, 16] ....

J. Doyle. Rationality and Its Roles in Reasoning. In Proceedings of the Eight National Conference on Arti cial Intelligence, pages 1093-1100, Menlo Park, California, 1990. American Association for Arti cial Intelligence.

....Y axis is F0, X axis is time. 3.2. 2 Deliberation Rejections Deliberation rejections are a way of rejecting proposals that rely on default inferences about the deliberative processes by which an agent evaluates the potential benefit or utility of pursuing a course of action [Bratman et al. 1988; Doyle, 1992] Deliberation inferences are the action parallel of epistemic inferences. Where epistemic inferences are concerned with belief and truth, deliberative inferences involve intentions and the desirability, utility or expected payoff of one potential intention when compared with another. Rejections ....

.... some shared goal of finding a solution to the caller s problem [Grosz and Sidner, 1990; Walker and Whittaker, 1990; Traum, 1994; Chu Carrol and Carberry, 1994] Given this shared goal, they then deliberate about which intentions to adopt as means for satisfying that goal [Bratman et al. 1988; Doyle, 1992] The degreei in the consequent of 42 is defined by possible courses of action, or alternate potential plans that a conversant may consider, and the degree of the utility of the proposed course of action in comparison with other alternate means. These inference rules are default inference rules ....

Jon Doyle. Rationality and its roles in reasoning. Computational Intelligence, 8(2):376-409, 1992.

.... since then, the concept of imprecise computation has been applied to solve several diverse problems [YAT02, MLFL94, HC95, LKL01] The idea of anytime algorithms is also similar to the notion of rationality in automated reasoning and search investigated by Russel et al. in [RW89, RW91] Doyle in [Doy90] and D Ambrosio in [D A89] Real time computational tasks that are anytime algorithms, prove to be useful in the design of real time systems. The property of anytime algorithms to trade computational time for decision quality results in optimal performance of real time systems [DB88, Hor87, ....

J. Doyle. Rationality and Its Roles in Reasoning. In Proceedings of the Eight National Conference on Artificial Intelligence, pages 1093--1100, Menlo Park, California, 1990. American Association for Artificial Intelligence.

....itself is normally unavoidable, leading to a deliberative agent. Since the resources available to the agent (in terms of computational power, memory, etc. are bounded, the resulting behavior may be imperfect hence the distinction between bounded and perfect rationality [Good, 1971; Simon, 1982; Doyle, 1990; Russell and Wefald, 1991] Bounded rationality is a desired property of intelligent agents since it provides a good evaluation criteria and since it establishes a formal framework to analyze agents. This paper addresses several fundamental questions related to models of bounded rationality: ....

J. Doyle. Rationality and its roles in rea- soning. Proceedings of the Eighth National Conference on Artificial Intelligence, pp. 1093-1100, Boston, Massachusetts, 1990.

.... heuristic strategies for achieving DELIBEIAq IoN Based intentions[9] 2 Deliberation DELIBERATION as a component of a theory of intention in discourse is functionally related to the theory of economic rationality, which in recent years has augmented the INFORMATION based (logical) view of action [3]. DELIBERATION iS the process by which an agent explicitly or implicitly evaluates a set of alternates in order to decide what s he wants to believe and what course of action s he wants to pursueJ Thus agents deliberate about whether as well as how to revise their beliefs and intentions as they ....

Jou Doyle. Rationality and its roles in reasoning. Computational Intelligence, November 1992.

....use MOTIVATION for discourse planning The effect of presentational relations is always to increase H s belief, de sire, or intention. Thus we will need (in the case of MOTIVATION) some sort of representation of degree of desire. In a first attempt at using MOTIVATION, we will use utility theory [6] and simply associate utilities with proposed actions. Under this view, an agent s strength of desire to perform an action is the utility he or she believes performing the action will yield, where utility is a quantifiable variable. In section 6 we will discuss the limitations of this approach. ....

....agent kim option 45: put act (agent bill green couch room 1) 4: KIM: No, instead let s put the purple couch in the study. reject agent ldm agent bill option 56: put act (agentldm purple couch robin l) On receiving a proposal, an agent deliberates whether to ccrT or R. CT the proposal [6]. Each furniture The generation of the gloss was not a focus of this study and was done via adhoc methods. item has a value that contributes to an evaluation of the final plan. The values on the furniture items range from 10 to 56, and both agents furniture items range over these values. Agents ....

J. Doyle. Rationality and its roles in reasoning. Computational Intelligence, November 1992.

....address what we regard as the basic features of active logics and how they differ from other approaches to reasoning. Chief among these are: limited reasoning, temporal reasoning, meta reasoning, real time planning, reasoning engines, indexicality, and belief revision. 1.2. 1 Limited Reasoning Doyle [ Doyle, 1992 ] discusses the complementary roles that the economics theory of rationality and mathematical logic play in the development of rational automated agents. In particular Doyle explores some major limitations of agents that influence their rationality. Active logic was developed to overcome such ....

J. Doyle. Rationality and its roles in reasoning. Computational Intelligence, 8(2):376--409, 1992.

....Answers to these basic questions are needed if robust and reliable agent based systems are to be developed. Designers want their agents to be rational and to do the right thing [16] To this end, a major strand of research has adopted the economic viewpoint and looked at self interested agents [7] that consider what action to take solely in terms of its worth to themselves. However, this is only part of the story. When an agent is situated in a multi agent context, its actions can have non local effects. For example, the actions of different agents can conflict or result in duplication of ....

J. Doyle. Rationality and its role in reasoning. Computational Intelligence, 8(3):376--409, 1992.

....Not much work has been done based on results from the area of multi criteria decision aid (MCDA) cf. 3] for handling such problems. Other aspects of decision theory, however, have influenced the area of MASs (cf. 4] partly as a result of philosophical aspects of agent rationality [5], and partly because of interest in extending the principle of maximising the expected utility in efficient real life applications [6] The viewpoint taken in this paper is that MCDA is well suited for the treatment of systems of cooperating agents. A typical multi criteria decision model is ....

J. Doyle, Rationality and its Roles in Reasoning, Computational Intelligence 8:2 (1992) 376-- 409.

....and emotions are useful in designing competent arti cial agents that are to operate within complex uncertain environments populated by other arti cial and human agents. Our work draws on and combines an emerging technology of rational agent design from arti cial intelligence on the one hand [7, 9, 28, 34], with research on human emotions in cognitive science and psychology on the other hand [8, 11, 15, 16, 17, 20, 25, 30, 32, 31] Our work accepts the decision theoretic paradigm of rationality, according to which a rational agent should behave so as to maximize the expected utility of its actions ....

.... research on human emotions in cognitive science and psychology on the other hand [8, 11, 15, 16, 17, 20, 25, 30, 32, 31] Our work accepts the decision theoretic paradigm of rationality, according to which a rational agent should behave so as to maximize the expected utility of its actions (see [3, 9, 28] and other references therein) The expected utilities of the alternative courses of action are computed based on their possible consequences, the desirability of these consequences to the agent, 1 and the probabilities with which these consequences are thought by the agent to obtain. 2 We aim ....

[Article contains additional citation context not shown here]

Jon Doyle. Rationality and its role in reasoning. Computational Intelligence, 8:376-409, 1992.

No context found.

Doyle J. (1992) Rationality and its roles in reasoning, Computational Intelligence 8(2), pp. 376--409.

No context found.

Doyle J. (1992) Rationality and its roles in reasoning, Computational Intelligence 8(2), pp. 376--409.

No context found.

J. Doyle. Rationality and Its Roles in Reasoning. Computational Intelligence, 8(2):376-409, 1992.

No context found.

Doyle, J. 1990. Rationality and it roles in reasoning. In AAAI, 1093--1100.

No context found.

J. Doyle, Rationality and Its Roles in Reasoning. Computational Intelligence, Vol. 8, 1992.

No context found.

J. Doyle. Rationality and its roles in reasoning. Computational Intelligence, 8(2):376--409, 1992.

No context found.

J. Doyle. Rationality and its role in reasoning. Computational Intelligence, 8:376--409, 1992.

No context found.

J. Doyle. Rationality and its roles in reasoning. Computational Intelligence, 8(2):376 -- 409, 1992.

No context found.

Jon Doyle. Rationality and its roles in reasoning. Computational Intelligence, 8(2):376-- 409, May 1992. 47

No context found.

J. Doyle. Rationality and its roles in reasoning. In Proceedings of the Eighth National Conference on Artificial Intelligence, pp. 1093--1100, Boston, Massachusetts, 1990.

First 50 documents  Next 50

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC