2,075 research outputs found
Bounded Situation Calculus Action Theories
In this paper, we investigate bounded action theories in the situation
calculus. A bounded action theory is one which entails that, in every
situation, the number of object tuples in the extension of fluents is bounded
by a given constant, although such extensions are in general different across
the infinitely many situations. We argue that such theories are common in
applications, either because facts do not persist indefinitely or because the
agent eventually forgets some facts, as new ones are learnt. We discuss various
classes of bounded action theories. Then we show that verification of a
powerful first-order variant of the mu-calculus is decidable for such theories.
Notably, this variant supports a controlled form of quantification across
situations. We also show that through verification, we can actually check
whether an arbitrary action theory maintains boundedness.Comment: 51 page
Abstraction in situation calculus action theories
We develop a general framework for agent abstraction based on the situation calculus and the ConGolog agent programming language. We assume that we have a high-level specification and a low-level specification of the agent, both repre- sented as basic action theories. A refinement mapping specifies how each high-level action is implemented by a low- level ConGolog program and how each high-level fluent can be translated into a low-level formula. We define a notion of sound abstraction between such action theories in terms of the existence of a suitable bisimulation between their respective models. Sound abstractions have many useful properties that ensure that we can reason about the agentâs actions (e.g., executability, projection, and planning) at the abstract level, and refine and concretely execute them at the low level. We also characterize the notion of complete abstraction where all actions (including exogenous ones) that the high level thinks can happen can in fact occur at the low level
Abstraction in situation calculus action theories
We develop a general framework for agent abstraction based on the situation calculus and the ConGolog agent programming language. We assume that we have a high-level specification and a low-level specification of the agent, both repre- sented as basic action theories. A refinement mapping specifies how each high-level action is implemented by a low- level ConGolog program and how each high-level fluent can be translated into a low-level formula. We define a notion of sound abstraction between such action theories in terms of the existence of a suitable bisimulation between their respective models. Sound abstractions have many useful properties that ensure that we can reason about the agentâs actions (e.g., executability, projection, and planning) at the abstract level, and refine and concretely execute them at the low level. We also characterize the notion of complete abstraction where all actions (including exogenous ones) that the high level thinks can happen can in fact occur at the low level
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
On First-Order Ό-Calculus over Situation Calculus Action Theories
In this paper we study verification of situation calculus action theories against first-order mu-calculus with quantification across situations. Specifically, we consider mu-La and mu-Lp, the two variants of mu-calculus introduced in the literature for verification of data-aware processes. The former requires that quantification ranges over objects in the current active domain, while the latter additionally requires that objects assigned to variables persist across situations. Each of these two logics has a distinct corresponding notion of bisimulation. In spite of the differences we show that the two notions of bisimulation collapse for dynamic systems that are generic, which include all those systems specified through a situation calculus action theory. Then, by exploiting this result, we show that for bounded situation calculus action theories, mu-La and mu-Lp have exactly the same expressive power. Finally, we prove decidability of verification of mu-La properties over bounded action theories, using finite faithful abstractions. Differently from the mu-Lp case, these abstractions must depend on the number of quantified variables in the mu-La formula
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
Hybrid Temporal Situation Calculus
The ability to model continuous change in Reiter's temporal situation
calculus action theories has attracted a lot of interest. In this paper, we
propose a new development of his approach, which is directly inspired by hybrid
systems in control theory. Specifically, while keeping the foundations of
Reiter's axiomatization, we propose an elegant extension of his approach by
adding a time argument to all fluents that represent continuous change.
Thereby, we insure that change can happen not only because of actions, but also
due to the passage of time. We present a systematic methodology to derive, from
simple premises, a new group of axioms which specify how continuous fluents
change over time within a situation. We study regression for our new temporal
basic action theories and demonstrate what reasoning problems can be solved.
Finally, we formally show that our temporal basic action theories indeed
capture hybrid automata
Progression and Verification of Situation Calculus Agents with Bounded Beliefs
We investigate agents that have incomplete information and make decisions based on their beliefs expressed as situation calculus bounded action theories. Such theories have an infinite object domain, but the number of objects that belong to fluents at each time point is bounded by a given constant. Recently, it has been shown that verifying temporal properties over such theories is decidable. We take a first-person view and use the theory to capture what the agent believes about the domain of interest and the actions affecting it. In this paper, we study verification of temporal properties over online executions. These are executions resulting from agents performing only actions that are feasible according to their beliefs. To do so, we first examine progression, which captures belief state update resulting from actions in the situation calculus. We show that, for bounded action theories, progression, and hence belief states, can always be represented as a bounded first-order logic theory. Then, based on this result, we prove decidability of temporal verification over online executions for bounded action theories. © 2015 The Author(s
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