Halpern, J. Y., Moses, Y., and Vardi, M. Y. (1994) Algorithmic knowledge. Theoretical Aspects of Reasoning about Knowledge: Proc. Fifth Conference. San Francisco: Morgan Kaufmann, 255 -- 266. Home/Search Document Details and Download
Summary Related Articles Check |
This paper is cited in the following contexts:
Grounding Knowledge and Action Selection in Agent-Based Systems - Alechina, Logan (Correct)
....intentional notions . In this paper we are concerned with ascribing knowledge to agents. Such knowledge is often termed implicit knowledge and includes as a subset the agent s explicit knowledge, i.e. the knowledge the agent has access to and can answer questions about (as studied in e.g. [7]) However if we are ascribing knowledge we then have to define precisely what we mean by the agent knows that # . In many cases, the semantics of agent states is simply stipulated by the designer, who assigns a particular meaning to a particular state or set of states, and strives to design the ....
Joseph Y. Halpern, Yoram Moses, and Moshe Y. Vardi. Algorithmic knowledge. In Ronald Fagin, editor, Theoretical Aspects of Reasoning about Knowledge: Proceedings of the Fifth Conference (TARK 1994.
Simulative Inference about Nonmonotonic Reasoners - Kaplan (1998) (Correct)
....agents in that model must believe all of the logical consequences of their beliefs. Our computational model of belief is one of many later alternatives that model believers in a more realistic (i.e. computationally feasible) way. The model of algorithmic knowledge of Halpern, Moses, and Vardi [2] is similar to ours in that it models an agent s belief state as the state of a computational mechanism, and its belief set as the set of sentences accepted by that mechanism in its current state. Halpern et al. do not treat the subject of simulative reasoning. Konolige s deduction model [6] is ....
Joseph Y. Halpern, Yoram Moses, and Moshe Y. Vardi. Algorithmic knowledge. In Ronald Fagin, editor, Theoretical Aspects of Reasoning about Knowledge: Proc. Fifth Conference, pages 255--266, San Francisco, 1994. Morgan Kaufmann.
A Computational Model of Belief - Kaplan, Schubert (2000) (Correct)
....we leave the reasoning method as a parameter of the model. The main results we have reached depend on the reasoning method being constrained in certain ways, but these constraints are weak enough that the results apply to an interesting range of different mechanisms. Halpern, Moses, and Vardi [8] describe a model of algorithmic knowledge that is similar to our model in that an agent s beliefs are taken to be the sentences that the agent s A.N. Kaplan, L.K. Schubert Artificial Intelligence 120 (2000) 119 160 149 reasoning algorithm can verify given the information encoded in the ....
J.Y. Halpern, Y. Moses, M.Y. Vardi, Algorithmic knowledge, in: R. Fagin (Ed.), Theoretical Aspects of Reasoning about Knowledge: Proc. Fifth Conference, Morgan Kaufmann, San Francisco, CA, 1994, pp. 255--266.
How to represent knowledge and belief? (Extended Abstract) - Duc (1996) (Correct)
....[11] 5] are not applicable. Neither does the awareness approach ( 3] work: it is quite implausible to explain that agent 3 does not know A a because he is not aware of some (arithmetical) sentences. We can also see easily that the deduction model ( 10] and the algorithmic knowledge approach ([7]) cannot offer any adequate analysis: it is not plausible to assume that the blue army use an incomplete deductive system or apply an incomplete algorithm to deduce the secret key. Certainly the agents 1 and 2 (the attacking generals) would not make the mistake to make any of the assumptions we ....
J. Y. Halpern, Y. Moses, and M. Y. Vardi. Algorithmic knowledge. In R. Fagin, editor, Theoretical Aspects of Reasoning about Knowledge: Proc. Fifth Conference, pages 255--266, San Francisco, 1994. Morgan Kaufman.
Simulative Inference in a Computational Model of Belief - Kaplan, Schubert (1997) (Correct)
....of information, namely the fact that the agent posed a query to its belief machine by a certain time. Since the two simulative techniques are applicable in different circumstances, a single system could make use of both. This possibility is discussed further in Section 4. Halpern, Moses, and Vardi [7] describe a very general model in which each agent has a local state l and an algorithm A. The algorithm takes a local state and a sentence as input, and answers yes, no, or . An agent s explicit beliefs are those sentences for which A( l) yes. The local state is analogous to our ....
.... for which A( l) yes. The local state is analogous to our belief state, and the algorithm A is analogous to our ASK, but there is nothing in their model analogous to our TELL; that is, the model does not describe how agents move from one local state to another. There is no discussion in [7] of conditions under which simulative inference is sound. Ballim and Wilks [2] contend that there can be no satisfactory semantics for a formal logic of belief. Logical semantics, they claim, is a heap view of belief, meaning that all beliefs are lumped together in an unstructured heap of ....
Joseph Y. Halpern, Yoram Moses, and Moshe Y. Vardi. Algorithmic knowledge. In Ronald Fagin, editor, Theoretical Aspects of Reasoning about Knowledge: Proc. Fifth Conference, pages 255--266, San Francisco, 1994. Morgan Kaufmann.
Knowledge-Based Programs - Fagin, Halpern, Moses, Vardi (1995) (24 citations) Self-citation (Halpern Moses Vardi) (Correct)
....as a standard program, will give us a powerful tool for program development. We discuss this idea in detail and provide several examples in the full paper. Two extensions of the idea of knowledge based programs appear in the literature. One is the notion of programs based on algorithmic knowledge [HMV94], in which knowledge is assumed to be computed by a specific algorithm. Another is the notion of knowledge oriented programs [MK93] Recall that the actions in knowledgebased programs are standard actions, just as in standard programs. Based on an earlier draft of this paper and of [FHMV95] Moses ....
J. Y. Halpern, Y. Moses, and M. Y. Vardi. Algorithmic knowledge. In R. Fagin, editor, Theoretical Aspects of Reasoning about Knowledge: Proc. Fifth Conference, pages 255--266. Morgan Kaufmann, San Francisco, Calif., 1994.
Reasoning About Knowledge: A Survey - Halpern (1995) (3 citations) Self-citation (Halpern) (Correct)
....everyone knows that : Just as common knowledge corresponds to simultaneous coordination, ffl common knowledge corresponds to coordinating to within ffl time units. Further discussion of variants of common knowledge can be found in [Dwork and Moses 1990; Fischer and Immerman 1986; Fagin and Halpern 1994; Halpern and Moses 1990; Halpern, Moses, and Waarts 1990; Moses and Tuttle 1988; Neiger and Toueg 1993; Panangaden and Taylor 1992] This approach still does not explain the pervasive feeling that we do (occasionally) attain common knowledge. The second approach attempts to deal with this issue. ....
....the awareness set at state s would consist of those formulas whose truth the agent can figure out given the information it has acquired at state s. This interpretation has been investigated in the context of the model for multi agent systems discussed in the previous section in work of Halpern, Moses, and Vardi [1994], which in turn is based on earlier work of Moses [1988] The key idea is to add to the agent s local state the algorithm that he is using to compute his knowledge. Thus, the agent s local state at a point (r; m) has the form (A; where A is his algorithm and is the rest of his local state. ....
[Article contains additional citation context not shown here]
Halpern, J. Y., Y. Moses, and M. Y. Vardi (1994). Algorithmic knowledge. In R. Fagin (Ed.), Theoretical Aspects of Reasoning about Knowledge: Proc. Fifth Conference, pp. 255--266. San Francisco, Calif.: Morgan Kaufmann.
Simulative Inference in a Computational Model of Belief - Kaplan, Schubert (1997) (Correct)
No context found.
Halpern, J. Y., Moses, Y., and Vardi, M. Y. (1994) Algorithmic knowledge. Theoretical Aspects of Reasoning about Knowledge: Proc. Fifth Conference. San Francisco: Morgan Kaufmann, 255 -- 266.
A Knowledge based semantics of messages - Parikh, Ramanujam (2003) (1 citation) (Correct)
No context found.
Halpern, J., Moses, Y., and Vardi, M., "Algorithmic knowledge", TARK V, Theoretical Aspects of Reasoning about Knowledge, 1994, 255-266.
View-Based Explicit Knowledge - Ramanujam (1998) (Correct)
No context found.
Halpern, J., Moses, Y., and Vardi, M., "Algorithmic knowledge", TARK V, Theoretical Aspects of Reasoning about Knowledge, 1994, 255-266.
Lecture Notes on Modal Logic in Computer Science - Ramanujam (1997) (Correct)
No context found.
Halpern, J., Moses, Y., and Vardi, M., "Algorithmic knowledge", TARK V, Theoretical Aspects of Reasoning about Knowledge, 1994, 255-266.
Knowledge, Views and Model Checking - Ramanujam (Correct)
No context found.
Halpern, J., Moses, Y., and Vardi, M., "Algorithmic knowledge", TARK V, Theoretical Aspects of Reasoning about Knowledge, 1994, 255-266.
Local knowledge assertions in a changing world (Extended Abstract) - Ramanujam (Correct)
No context found.
Halpern, J., Moses, Y., and Vardi, M., "Algorithmic knowledge", TARK V, Theoretical Aspects of Reasoning about Knowledge, 1994, 255-266.
Simulative Inference in a Computational Model of Belief - Aaron Kaplan (1997) (Correct)
No context found.
Halpern, J. Y., Moses, Y., and Vardi, M. Y. (1994). Algorithmic knowledge. In Fagin, R., editor, Theoretical Aspects of Reasoning about Knowledge: Proc. Fifth Conference, pages 255--266, San Francisco. Morgan Kaufmann.
A Discussion on Explicit Knowledge - Ramanujam (1996) (Correct)
No context found.
Halpern, J., Moses, Y., and Vardi, M., "Algorithmic knowledge", TARK V, Theoretical Aspects of Reasoning about Knowledge, 1994, 255-266.
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