Christian Becker-Asano

[B]elievable [A]ndroids

Dynamic Epistemic Logic

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Conditional Epistemic Planning (Mikkel Birkegaard Andersen, Thomas Bolander, Martin Holm Jensen, 2012)
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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Epistemic planning for single- and multi-agent systems (Thomas Bolander, Mikkel Birkegaard Andersen, 2011)
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 en vironment 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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A logic for reasoning 0about counterfactual emotions (Emiliano Lorini, François Schwarzentruber, 2010)
The aim of this work is to propose a logical framework for the specification of cognitive emotions that are based on counterfactual reasoning about agents' choices. The prototypical counterfactual emotion is regret. In order to meet this objective, we exploit the well-known STIT logic (Belnap et al. (2001) [9], Horty (2001) [30], Horty and Belnap (1995) [31]). STIT logic has been proposed in the domain of formal philosophy in the nineties and, more recently, it has been imported into the field of theoretical computer science where its formal relationships with other logics for multi-agent systems such as ATL and Coalition Logic (CL) have been studied. STIT is a very suitable formalism to reason about choices and capabilities of agents and groups of agents. Unfortunately, the version of STIT with agents and groups has been recently proved to be undecidable and not finitely axiomatizable. In this work we study a decidable and finitely axiomatizable fragment of STIT with agents and groups which is sufficiently expressive for our purpose of formalizing counterfactual emotions. We call dfSTIT our STIT fragment. After having extended dfSTIT with knowledge modalities, in the second part of article, we exploit it in order to formalize four types of counterfactual emotions: regret, rejoicing, disappointment, and elation. At the end of the article we present an application of our formalization of counterfactual emotions to a concrete example.

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