An Internal Version of Epistemic Logic

Aucher, Guillaume

doi:10.1007/s11225-010-9227-9

Cited by 20 publications

(30 citation statements)

References 15 publications

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“…This is related to the distinction made in e.g. (Aucher, 2010;Fagin et al, 1995). Note that in a local state (M, W d ) for agent i, it is possible to have a pair of nodes w, v ∈ W d with (w, v) ∈ R i .…”

Section: Definition 2 (Truth In An Epistemic Modelmentioning

confidence: 80%

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Epistemic planning for single- and multi-agent systems

Bolander

Andersen

2011

Journal of Applied Non-Classical Logics

174

215

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ABSTRACT. In this paper, we investigate the use of event models for automated planning. Event models are the action defining structures used to define a semantics for dynamic epistemic logic. Using event models, two issues in planning can be addressed: Partial observability of the environment and knowledge. In planning, partial observability gives rise to an uncertainty about the world. For single-agent domains, this uncertainty can come from incomplete knowledge of the starting situation and from the nondeterminism of actions. In multi-agent domains, an additional uncertainty arises from the fact that other agents can act in the world, causing changes that are not instigated by the agent itself. For an agent to successfully construct and execute plans in an uncertain environment, the most widely used formalism in the literature on automated planning is "belief states": sets of different alternatives for the current state of the world. Epistemic logic is a significantly more expressive and theoretically better founded method for representing knowledge and ignorance about the world. Further, epistemic logic allows for planning according to the knowledge (and iterated knowledge) of other agents, allowing the specification of a more complex class of planning domains, than those simply concerned with simple facts about the world. We show how to model multi-agent planning problems using Kripke-models for representing world states, and event models for representing actions. Our mechanism makes use of slight modifications to these concepts, in order to model the internal view of agents, rather than that of an external observer. We define a type of planning domain called epistemic planning domains, a generalisation of classical planning domains, and show how epistemic planning can successfully deal with partial observability, nondeterminism, knowledge and multiple agents. Finally, we show epistemic planning to be decidable in the single-agent case, but only semi-decidable in the multi-agent case.

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Section: Definition 2 (Truth In An Epistemic Modelmentioning

confidence: 80%

“…In an epistemic state (M, w), w denotes the actual world. Epistemic states provide a model of the world from an external point of view, where the modeler is assumed to be an omniscient and external observer of the epistemic situation (Aucher, 2010). Thus, the modeler knows which is the actual world.…”

Section: Definition 2 (Truth In An Epistemic Modelmentioning

confidence: 99%

Epistemic planning for single- and multi-agent systems

Bolander

Andersen

2011

Journal of Applied Non-Classical Logics

174

215

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“…We call this the internal perspective-the modeller is modelling itself. The internal perspective is discussed thoroughly in [1,10]. Generally, an agent using epistemic models to model its own knowledge and ignorance, will not be able to point out the actual world.…”

Section: Conditional Plans In Delmentioning

confidence: 99%

Conditional Epistemic Planning

Andersen

Bolander

Jensen

2012

Logics in Artificial Intelligence

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Abstract. Recent work has shown that Dynamic Epistemic Logic (DEL) offers a solid foundation for automated planning under partial observability and non-determinism. Under such circumstances, a plan must branch if it is to guarantee achieving the goal under all contingencies (strong planning). Without branching, plans can offer only the possibility of achieving the goal (weak planning). We show how to formulate planning in uncertain domains using DEL and give a language of conditional plans. Translating this language to standard DEL gives verification of both strong and weak plans via model checking. In addition to plan verification, we provide a tableau-inspired algorithm for synthesising plans, and show this algorithm to be terminating, sound and complete.

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“…This informal analysis of the notion of strong belief is formally confirmed by the fact that the axiom B(Bφ → φ) is valid in the KD45 logic of belief, and also by the fact that the axiom Bφ → φ, which is a key axiom of the notion of knowledge, is an axiom of the internal version of epistemic logic (Aucher, 2010).…”

Section: Principles Of Interaction With Strong Beliefmentioning

confidence: 76%

“…In that respect, an internal approach seems to be more appropriate since, in this context, the agent needs to reason from its own internal point of view. For the internal approach, the logic of belief is S5, as proved in (Aucher, 2010) and (Arlo-Costa, 1999) (for the notion of full belief ). 15…”

Section: Principles Of Strong Beliefmentioning

confidence: 95%

Principles of Knowledge, Belief and Conditional Belief

Aucher

2014

Logic, Argumentation &Amp; Reasoning

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International audienceWe review and examine in this paper the validity of the different axioms (and inference rules) of knowledge and belief and relating knowledge to belief which have been proposed in the epistemic !epistemic logic literature. In doing so, we encounter many of the problems that epistemic !epistemic logic has had to face in its relatively short (modern) history and provide relevant pointers for more details. We also contribute to this area by providing conditions under which the notion of belief can be formally defined in terms of knowledge , and vice versa. We also prove that certain convoluted axioms dealing only with the notion of knowledge can be derived from understandable interaction axioms relating knowledge and conditional belief

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An Internal Version of Epistemic Logic

Cited by 20 publications

References 15 publications

Epistemic planning for single- and multi-agent systems

Epistemic planning for single- and multi-agent systems

Conditional Epistemic Planning

Principles of Knowledge, Belief and Conditional Belief

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