Temporal Logic with Capacity Constraints

Dixon, Clare; Fisher, Michael; Konev, Boris

doi:10.1007/978-3-540-74621-8_11

Cited by 11 publications

(17 citation statements)

References 18 publications

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“…The atLeast predicate places a minimum constraint on the number of instances of positive predicates, whilst atMost places a maximum constraint on the number of instances of positive predicates in a given temporal state, in the style of the capacity constraints described by [10]. Besides providing the developer with the ability to influence an agent's reasoning, when applied judiciously atMost and atLeast can simplify the fragment of the logic considered and hence can increase the execution performance of a METATEM agent.…”

Section: Strategies and Deliberationmentioning

confidence: 99%

Executing Logical Agent Specifications

Fisher

Hepple

2009

Multi-Agent Programming

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Many agent-oriented programming languages are based on the Prolog-like logical goal reduction approach where rules are used to reduce, in a depth-first way, a selected goal. The ability of agents to change between goals means that such languages often overlay the basic computational engine with a mechanism for dynamically changing which goal is selected.Our approach is different. The basic computational approach we use is that of model building for logical formulae, but the underlying formulae are temporal. This allows us to capture the dynamic nature of the agent explicitly. In addition, the temporal basis provides us with ways of having multiple active 'goals' and being able to achieve several at once. As in most agent-oriented languages deliberation is used to choose between goals when not all can be satisfied at once. This basic execution of temporal formulae provides us with the foundation for agent programming. In order to deal with multi-agent systems in an equally straightforward way we also incorporate a very simple, but flexible, model of organisational structuring.These two aspects provide the core of the language implemented. There are, however, many extensions that have been proposed, some of which have been implemented, and all of which are mentioned in this article. These include varieties of agent belief, resourcebounded reasoning, the language's use as a coordination language, and the use of contextual constraints.

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Section: Strategies and Deliberationmentioning

confidence: 99%

Executing Logical Agent Specifications

Fisher

Hepple

2009

Multi-Agent Programming

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“…The authors of this paper have considered decision procedures for propositional linear-time temporal logics allowing the input of constrained sets in [5,6]. Both assume the temporal formulae are in a normal form with clauses relating to the initial moment, conditions on the next moment given the current state, and eventualities.…”

Section: Related and Further Workmentioning

confidence: 99%

“…This is different than the approach here where, as usual, the tableau algorithm can be applied to any XL5 formula and does not require translation into normal form. In [5] a tableau-like structure (known as an Incremental Behaviour Graph) is constructed and allows more expressive constraints than we do here (eg exactly n from a set holding or less than n from a set holding). The paper [6] defines a resolution calculus.…”

Section: Related and Further Workmentioning

confidence: 99%

“…Normal unconstrained propositions were also allowed. Not only did this allow the concise specification of examples such as the representation of automata, basic planning problems, and agent negotiation protocols, but also greatly reduced the complexity of the associated decision procedure [5,6]. Essentially, this is because (as the name suggests) exactly one element of each "exactly one" set must be satisfied at every temporal state.…”

Section: Introductionmentioning

confidence: 99%

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Taming the Complexity of Temporal Epistemic Reasoning

Dixon

Fisher

Konev

2009

Frontiers of Combining Systems

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Abstract. Temporal logic of knowledge is a combination of temporal and epistemic logic that has been shown to be very useful in areas such as distributed systems, security, and multi-agent systems. However, the complexity of the logic can be prohibitive. We here develop a refined version of such a logic and associated tableau procedure with improved complexity but where important classes of specification can still be described. This new logic represents a combination of an "exactly one" temporal logic with an S5 multi-modal logic again restricted to the "exactly one" form.

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“…These logics, called TLX [14,16] and TLC [15], not only reduce the size of the temporal specifications we use but also significantly reduce the complexity of the decision problem for such specifications if the specifications are in or near SNF. Note that this approach involves reasoning in the presence of constraints rather than reasoning about them.…”

Section: Applying Constraintsmentioning

confidence: 99%