Figure 1 - uploaded by François Schwarzentruber
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Graphical user interface of Hintikka's world.
Source publication
Hintikka's World is a graphical and pedagogical tool that shows how artificial agents can reason about higher-order knowledge. In this demonstration paper, we present the implementation of symbolic models in Hintikka's World. They enable the tool to scale, by helping it to face the state explosion, which makes it possible to provide examples featur...
Contexts in source publication
Context 1
... only pedagogical tool explaining these models that we are aware of is Hintikka's world, which was presented at ECAI-IJCAI 2018 [Schwarzentruber, 2018]. Hintikka's world is a proof of concept of a graphical user interface that represents Kripke models by comic strips, as shown in Figure 1. It enables the user to explore the mental states of agents. ...
Citations
... In many applications, artificial agents make decisions in a partially observable environment. They follow a policy, which is sometimes specified manually by a policy designer, sometimes automatically computed (and sometimes partly 25 specified manually, and completed automatically). At an abstract level, such policies (or plans) in partially observable domains are mappings from belief states to actions. ...
... A KBP is said to be well-formed if (i) all its subprograms are well-formed and (ii) it is ε, it takes an action for sure, 7 An animation of progression of belief states in Minesweeper and other domains is available at http://hintikkasworld.irisa.fr [66,25]. We are now ready to formally define how well-formed KBPs are executed. ...
We suggest to express policies for contingent planning by knowledge-based programs (KBPs). KBPs, introduced by Fagin et al. [Reasoning about Knowledge, MIT Press, 1995], are high-level protocols describing the actions that the agent should perform as a function of their current knowledge: branching conditions are epistemic formulas that are interpretable by the agent. The main aim of our paper is to show that KBPs can be seen as a succinct language for expressing policies in single-agent contingent planning.
KBP are conceptually very close to languages used for expressing policies in the partially observable planning literature: like them, they have conditional and looping structures, with actions as atomic programs and Boolean formulas on beliefs for choosing the execution path. Now, the specificity of KBPs is that branching conditions refer to the belief state and not to the observations.
Because of their structural proximity, KBPs and standard languages for representing policies have the same power of expressivity: every standard policy can be expressed as a KBP, and every KBP can be “unfolded” into a standard policy. However, KBPs are more succinct, more readable, and more explainable than standard policies. On the other hand, they require more online computation time, but we show that this is an unavoidable tradeoff. We study knowledge-based programs along four criteria: expressivity, succinctness, complexity of online execution, and complexity of verification.
