20,880 research outputs found
Situation awareness and ability in coalitions
This paper proposes a discussion on the formal links between the Situation Calculus and the semantics of interpreted systems as far as they relate to Higher-Level Information Fusion tasks. Among these tasks Situation Analysis require to be able to reason about the decision processes of coalitions. Indeed in higher levels of information fusion, one not only need to know that a certain proposition is true (or that it has a certain numerical measure attached), but rather needs to model the circumstances under which this validity holds as well as agents' properties and constraints. In a previous paper the authors have proposed to use the Interpreted System semantics as a potential candidate for the unification of all levels of information fusion. In the present work we show how the proposed framework allow to bind reasoning about courses of action and Situation Awareness. We propose in this paper a (1) model of coalition, (2) a model of ability in the situation calculus language and (3) a model of situation awareness in the interpreted systems semantics. Combining the advantages of both Situation Calculus and the Interpreted Systems semantics, we show how the Situation Calculus can be framed into the Interpreted Systems semantics. We illustrate on the example of RAP compilation in a coalition context, how ability and situation awareness interact and what benefit is gained. Finally, we conclude this study with a discussion on possible future works
Hierarchical agent supervision
Agent supervision is a form of control/customization where a supervisor restricts the behavior of an agent to enforce certain requirements, while leaving the agent as much autonomy as possible. To facilitate supervision, it is often of interest to consider hierarchical models where a high level abstracts over low-level behavior details. We study hierarchical agent supervision in the context of the situation calculus and the ConGolog agent programming language, where we have a rich first-order representation of the agent state. We define the constraints that ensure that the controllability of in-dividual actions at the high level in fact captures the controllability of their implementation at the low level. On the basis of this, we show that we can obtain the maximally permissive supervisor by first considering only the high-level model and obtaining a high- level supervisor and then refining its actions locally, thus greatly simplifying the supervisor synthesis task
cc-Golog: Towards More Realistic Logic-Based Robot Controllers
High-level robot controllers in realistic domains typically deal with
processes which operate concurrently, change the world continuously, and where
the execution of actions is event-driven as in ``charge the batteries as soon
as the voltage level is low''. While non-logic-based robot control languages
are well suited to express such scenarios, they fare poorly when it comes to
projecting, in a conspicuous way, how the world evolves when actions are
executed. On the other hand, a logic-based control language like \congolog,
based on the situation calculus, is well-suited for the latter. However, it has
problems expressing event-driven behavior. In this paper, we show how these
problems can be overcome by first extending the situation calculus to support
continuous change and event-driven behavior and then presenting \ccgolog, a
variant of \congolog which is based on the extended situation calculus. One
benefit of \ccgolog is that it narrows the gap in expressiveness compared to
non-logic-based control languages while preserving a semantically well-founded
projection mechanism
Abstraction of Agents Executing Online and their Abilities in the Situation Calculus
We develop a general framework for abstracting online behavior of an agent that may acquire new knowledge during execution (e.g., by sensing), in the situation calculus and ConGolog. We assume that we have both a high-level action theory and a low-level one that represent the agent's behavior at different levels of detail. In this setting, we define ability to perform a task/achieve a goal, and then show that under some reasonable assumptions, if the agent has a strategy by which she is able to achieve a goal at the high level, then we can refine it into a low-level strategy to do so
Logic-Based Specification Languages for Intelligent Software Agents
The research field of Agent-Oriented Software Engineering (AOSE) aims to find
abstractions, languages, methodologies and toolkits for modeling, verifying,
validating and prototyping complex applications conceptualized as Multiagent
Systems (MASs). A very lively research sub-field studies how formal methods can
be used for AOSE. This paper presents a detailed survey of six logic-based
executable agent specification languages that have been chosen for their
potential to be integrated in our ARPEGGIO project, an open framework for
specifying and prototyping a MAS. The six languages are ConGoLog, Agent-0, the
IMPACT agent programming language, DyLog, Concurrent METATEM and Ehhf. For each
executable language, the logic foundations are described and an example of use
is shown. A comparison of the six languages and a survey of similar approaches
complete the paper, together with considerations of the advantages of using
logic-based languages in MAS modeling and prototyping.Comment: 67 pages, 1 table, 1 figure. Accepted for publication by the Journal
"Theory and Practice of Logic Programming", volume 4, Maurice Bruynooghe
Editor-in-Chie
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