A. S. Rao. Decision procedures for propositional linear-time Belief-Desire-Intention logics. In M. Wooldridge, J. P. Muller, and M. Tambe, editors, Intelligent Agents II (LNAI Volume 1037), pages 33-48. Springer-Verlag: Berlin, Germany, 1996.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....or KD45 is given in [28] This is essentially the combination of tableau methods for propositional linear time temporal logics [27] and that for the modal logics S5 and KD45 [11] It does not require the translation to any particular normal form. The work on proof methods for BDI logics given in [21, 22] give a tableau based proof method for the fusion of either linear or branchingtime (CTL or CTL ) with the modal logics KD45 for belief, and KD for desire and intention. We presented tableau algorithms (without the use of normal forms or explicit application of the interaction axioms) for temporal ....

A. S. Rao. Decision Procedures for Propositional Linear-Time Belief-Desire-Intention Logics. In M. Wooldridge, K. Fischer, P. Gmytrasiewicz, N. R. Jennings, J. P. Muller, and M. Tambe, editors, IJCAI95 Workshop on Agent Theories, Architectures, and Languages, pages 102--118, Montreal, Canada, August 1995.

....intentions. The third and final aspect of the Bm model is the logical component, which gives us a family of tools that allow us to reason about Bm agents. There have been several versions of Bm logic, starting in 1991 and culminating in Rao and Georgeff s 1998 paper on systems of BD logics [64, 68, 65, 66, 67, 61, 63]; a book length survey was published as [77] We focus on [77] Syntactically, BD logics are essentially branching time logics (aTE or aTE , depending on which version you are reading about) enhanced with additional modal operators Bel, Des, and Intend, for capturing the beliefs, desires, and ....

A. S. Rao. Decision procedures for propositional linear-time Belief-Desire-Intention logics. In M. Wooldridge, J.P. Miiller, and M. Tambe, editors, Intelligent Agents II (LNAI Volume 1037), pages 33 48. Springer-Verlag: Berlin, Germany, 1996.

....systems. Modal logics, in particular, are often used for this purpose and o er a number of advantages [20, 21] In the landscape of agent systems among the more well known agent formalisms with a modal avour are the seminal combination of dynamic logic and epistemic logic by [16] the BDI model [17, 18], the KARO framework [15, 21] and temporal logics of knowledge We thank C. Dixon, M Fisher and U. Hustadt for valuable discussions. This research is supported by EPSRC Research Grants GR M88761 and GR R92035. and belief [3, 6, 7] Examples of more recent work is the proposal of a modal logic ....

A. S. Rao. Decision procedures for propositional linear-time belief-desire-intention logics. In Proc. ATAL'95, vol. 1037 of LNAI, pp. 102-118. Springer, 1996.

....on two binary relations R 1 and R 2 . The above mentioned axioms and conditions together with a range of additional axioms and constructs characterizes a typical BDI system. The properties of soundness, completeness etc are defined via canonical Kripke structures and for a further account see [14] The point here is that the axiom systems for GOAL and BEL is a combination of other axiom systems and hence they are different. They can be considered as two different languages L 1 and L 2 with # 1 (BEL) and # 2 (GOAL) built up from the respective sets A 1 and A 2 of atoms and supported by the ....

A. S. Rao. Decision procedures for propositional linear-time belief- desire-intention logics. In Intelligent Agents Volume II, LNAI-1037, pages 33--48. Springer-Verlag, 1996.

....environment, continuously perceive and react to the external stimulus based on their internal mental states. Belief, desire and intention are the primary mental attitudes usually ascribed to an agent, which capture informational, motivational, and committal aspects of an agent, respectively[6, 12, 13, 16]. In addition, a set of plans specifying the behavioral patterns of an agent is also needed. 2.1 Modeling Mental Attitudes The knowledge database of an agent is composed of true facts (domainspeci c or general) about the world accumulated in its life time. The belief states of an agent re ect ....

Rao, A.S.: Decision procedures for propositional linear-time beliefdesire -intention logics. In: IJCAI'95 Workshop (ATAL), LNAI 1037, pages 33-48, Montreal, Canada, 1995.

.... the resolution method to the (comparatively simple) branching time temporal logic CTL [5] We here consider the extension of this approach to the more powerful branchingtime logic CTL that is now being applied, for example, within the specification and verification of multi agent systems [15]. The key elements of the method, namely the normal form, the concept of step resolution and the form of the temporal resolution rule, are introduced and justified with respect to CTL . Our approach follows the observation that, as the branching structures characterised by CTL consist of ....

A. S. Rao. Decision procedures for propositional linear-time Belief-Desire-Intention logics. In Intelligent Agents II (LNAI 1037). Springer-Verlag: Heidelberg, Germany, 1996.

....environment, continuously perceive and react to the external stimulus based on their internal mental states. Belief, desire and intention are the primary mental attitudes usually ascribed to an agent, which capture informational, motivational, and committal aspects of an agent, respectively[6, 12, 13, 16]. In addition, a set of plans specifying the behavioral patterns of an agent is also needed. The knowledge database of an agent is composed of true facts (domainspeci c or general) about the world accumulated in its life time. The belief states of an agent re ect its models perceived so far about ....

Rao, A.S.: Decision procedures for propositional linear-time beliefdesire -intention logics. In: IJCAI'95 Workshop (ATAL), LNAI 1037, pages 33-48, Montreal, Canada, 1995.

....or dynamic logic; Motivation modal logic of intention (KD) or desire (KD) Thus, the predominant approaches use relevant combinations. For example: Moore (Moore, 1990) combines propositional dynamic logic and a modal logic of knowledge (S5) the BDI framework (Rao and Georgeff, 1991; Rao, 1995) uses linear or branching temporal logic, together with modal logics of belief (KD45) desire (KD) and intention (KD) Halpern et al. Halpern and Vardi, 1989; Fagin et al. 1996) use linear and branching time temporal logics combined with a multi modal (S5) logic of knowledge; and the KARO ....

A. S. Rao. Decision Procedures for Propositional Linear-Time Belief-Desire-Intention Logics. In, M. Wooldridge, K. Fischer, P. Gmytrasiewicz, N. R. Jennings, J. P. M uller, and M. Tambe, editors, IJCAI95 Workshop on Agent Theories, Architectures, and Languages, pages 102--118, Montr eal, Canada, August 1995.

....leaving him with some choices. Likewise, our framework (via the notion of a temporal action state condition) allows us to specify and evaluate conditions that are true at some time point in a given set this is similar to disjunctive reasoning. Representation of Goals: The BDI agent architecture (Rao 1995; Rao and George 1991) has raised the point that agents might have goals and might need to reason with them. This has often been taken to mean that all agents must be able to construct plans. We take the position that the BDI model merely says that an agent development environment (such as the ....

Rao, A. S. (1995). Decision Procedures for Propositional Linear-Time BeliefDesire -Intention Logics. In M. Wooldridge, J. Muller, and M. Tambe (Eds.), Intelligent Agents II { Proceedings of the 1995 Workshop on Agent Theories, Architectures and Languages (ATAL-95), Volume 890 of LNAI, pp. 1-39. Berlin, Germany: Springer-Verlag.

....are available) BDI dates back to (Bratman, Israel, and Pollack 1988) PRS (procedural reasoning system, Georgeff and Lansky 1987) uses BDI. Applications: Space Shuttle (Diagnosis) Sydney Airport (air traffic control) BDI Logics: Rao and Georgeff 1991; Rao and Georgeff 1995; Rao 1995). 2.2 BDI Agents 45 Chapter 2: Three Basic Architectures Multi Agent Systems (6 Lectures) Sept. 2000, Bahia Blanca 2.3 Layered Architectures At least 2 layers: reactive (event driven) pro active (goal directed) 2.3 Layered Architectures 46 Chapter 2: Three Basic Architectures Multi Agent ....

Rao, A. S. (1995). Decision Procedures for Propositional Linear-Time Belief-Desire-Intention Logics. In M. Wooldridge, J. M uller, and M. Tambe (Eds.), Intelligent Agents II -- Proceedings of the 1995 Workshop on Agent Theories, Architectures and Languages (ATAL-95), Volume 890 of LNAI, pp.

....leaving him with some choices. Likewise, our framework (via the notion of a temporal action state condition) allows us to specify and evaluate conditions that are true at some time point in a given set this is similar to disjunctive reasoning. Representation of Goals: The BDI agent architecture (Rao 1995; Rao and George 1991) has raised the point that agents might have goals and might need to reason with them. This has often been taken to mean that all agents must be able to construct plans. We take the position that the BDI model merely says that an agent development environment (such as the ....

Rao, A. S. (1995). Decision Procedures for Propositional Linear-Time BeliefDesire -Intention Logics. In M. Wooldridge, J. Muller, and M. Tambe (Eds.), Intelligent Agents II { Proceedings of the 1995 Workshop on Agent Theories, Architectures and Languages (ATAL-95), Volume 890 of LNAI, pp. 1-39. Berlin, Germany: Springer-Verlag.

....days of agent research, an attempt was made to make the concept of agents more precise by means of logical systems. This e ort resulted in a number of mainly modal logics for the speci cation of agents which formally de ned notions like belief, goal, intention, etc. associated with agents [14, 19, 3, 4]. The relation of these logics with more practical approaches remains unclear, however, to this day. Several e orts to bridge this gap have been attempted. In particular, a number of agent programming languages have been developed to bridge the gap between theory and practice [13, 9] These ....

Anand S. Rao. Decision procedures for propositional linear-time belief-desire-intention logics. In M.J. Wooldridge, J.P. Muller, and M. Tambe, editors, Intelligent Agents II, volume 1037 of LNAI, pages 33-48. Springer, 1996.

....theoretical and logical investigations to more practical, implemented applications. As far as we know, however, there is still no uni ed account of agents which bridges the gap between the theoretical and more practical work on agents. First, formal logics, like BDI logic or the KARO framework ([21, 23, 25, 26], for example, are presented as a means for specifying intelligent agents. Nevertheless, so far no methodology has been provided for re ning such speci cations to known programming languages. Secondly, on the more practical side, a lot of agent architectures have been proposed. Although many ....

Anand S. Rao. Decision procedures for propositional linear-time beliefdesire -intention logics. In M.J. Wooldridge, J.P. Muller, and M. Tambe, editors, Intelligent Agents II, volume 1037 of LNAI, pages 33-48. Springer, 1996.

.... A tableau algorithm for the multi modal version of this logic and PTL combined with multi modal KD45 is presented in [25] Tableau based proof methods for Belief Desire Intention (BDI) Logics (combining linear or branching time temporal logics with the modal logics KD45 and KD) can be found in [20, 22]. Halpern, Vardi et al. provide complete axiomatisations for temporal logics of knowledge in [10] and consider complexity issues in [11] In this paper we outline a resolution based proof method for propositional linear time temporal logic (PTL) with multi modal logic S5. This work is an ....

.... of Km by the axioms 4, 5, B, D, T can be found in [17, 4] The translation based approach to modal theorem proving has been combined by the temporal reasoning part of the resolution method described in this paper in [13] Rao and Georgeff consider at tableau based proof methods for BDI logics in [20, 22]. Here they combine either linear or branching time temporal logics (CTL and CTL ) with the modal logics with the modal logics KD45 for belief and KD for desire and intention. In [22] interactions between the modal components are also considered. Tableau methods for PTL combined with multi modal ....

A. S. Rao. Decision Procedures for Propositional Linear-Time Belief-Desire-Intention Logics. In M. Wooldridge, K. Fischer, P. Gmytrasiewicz, N. R. Jennings, J. P. Muller, and M. Tambe, editors, IJCAI-95 Workshop on Agent Theories, Architectures, and Languages, pages 102--118, Montr'eal, Canada, August 1995.

....to embody similar intuitions, although they also mingle intentions and know how, as we have identified those concepts. We believe that the primitives developed herein will pay off when they begin to be incorporated into tools for reasoning about agents. Some useful results have been obtained by [19, 23, 29]. Complexity issues remain a challenge. This research area has been focused on conceptual issues in terms of the expressiveness to capture various cases, to obtain useful and avoid pernicious inferences. As these aspects are better understood, it will become appropriate to look for restricted ....

Anand S. Rao. Decision procedures for propositional linear-time belief-desire-intention logics. In IJCAI Workshop on Agent Theories, Architectures, and Languages, August 1995.

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A. S. Rao. Decision procedures for propositional linear-time belief-desire-intention logics. In Working notes of the IJCAI-95 Workshop on Agent Theories, Architectures, and Languages, Montreal, Canada, 1995.

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A. S. Rao. Decision procedures for propositional linear-time Belief-Desire-Intention logics. In M. Wooldridge, J. P. Muller, and M. Tambe, editors, Intelligent Agents II (LNAI Volume 1037), pages 33-48. Springer-Verlag: Berlin, Germany, 1996.

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A. S. Rao. Decision procedures for propositional linear-time belief-desire-intention logics, Proc. of ATAL95, LNAI 1037.

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Anand S. Rao. Decision procedures for propositional linear-time beliefdesire -intention logics. In Michael Wooldridge, Jorg P. Muller, and Milind Tambe, editors, Intelligent Agents II|Proceedings of the Second International Workshop on Agent Theories, Architectures, and Languages (ATAL'95), held as part of IJCAI'95, Montreal, Canada, August 1995.

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A. S. Rao. Decision Procedures for Propositional Linear-Time Belief-Desire-Intention Logics. In M. Wooldridge, K. Fischer, P. Gmytrasiewicz, N. R. Jennings, J. P. Muller, and M. Tambe, editors, IJCAI-95 Workshop on Agent Theories, Architectures, and Languages, pages 102-118, Montreal, Canada, August 1995.

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A. S. Rao. Decision procedures for propositional linear-time Belief-Desire-Intention logics. In M. Wooldridge, J. P. Muller, and M. Tambe, eds, Intelligent Agents II | Agent Theories, Architectures, and Languages, IJCAI'95 Workshop (ATAL-II), 32 Proceedings, vol. 1037 of Lecture Notes in Arti cial Intelligence, pp. 33-48. SpringerVerlag, 1996.

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Rao, A. S. (1995). Decision Procedures for Propositional Linear-Time Belief-Desire-Intention Logics. In M. Wooldridge, J. M uller, and M. Tambe (Eds.), Intelligent Agents II -- Proceedings of the 1995 Workshop on Agent Theories, Architectures and Languages (ATAL-95), Volume 890 of LNAI, pp.

No context found.

Rao, A. S. (1995). Decision Procedures for Propositional Linear-Time Belief-Desire-Intention Logics. In M. Wooldridge, J. M uller, and M. Tambe (Eds.), Intelligent Agents II -- Proceedings of the 1995 Workshop on Agent Theories, Architectures and Languages (ATAL-95), Volume 890 of LNAI, pp.

No context found.

Rao, A. S. (1995). Decision Procedures for Propositional Linear-Time Belief-Desire-Intention Logics. In M. Wooldridge, J. M uller, and M. Tambe (Eds.), Intelligent Agents II -- Proceedings of the 1995 Workshop on Agent Theories, Architectures and Languages (ATAL-95), Volume 890 of LNAI, pp.

No context found.

Rao, A. S. (1995). Decision Procedures for Propositional Linear-Time Belief-Desire-Intention Logics. In M. Wooldridge, J. M uller, and M. Tambe (Eds.), Intelligent Agents II -- Proceedings of the 1995 Workshop on Agent Theories, Architectures and Languages (ATAL-95), Volume 890 of LNAI, pp.

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