Computational Logic Foundations of KGP Agents

Kakas, Antonis C.; Mancarella, Paolo; Sadri, Fariba; Stathis, Kostas; Toni, Francesca

doi:10.1613/jair.2596

Cited by 33 publications

(22 citation statements)

References 50 publications

(64 reference statements)

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“…Contraries of assumptions represent reasons against actions (ā = r) or defeaters of defeasible premises (b = s,c = t). This interpretation of the given ABA framework is in line with existing approaches to model agents in computational logic (notably Kakas, Mancarella, Sadri, Stathis, & Toni, 2008;Kowalski & Sadri, 1999).…”

Section: Aba Frameworksupporting

confidence: 76%

A tutorial on assumption-based argumentation

Toni

2014

Argument & Computation

134

137

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We give an introductory tutorial to assumption-based argumentation (referred to as ABA) -a form of argumentation where arguments and attacks are notions derived from primitive notions of rules in a deductive system, assumptions and contraries thereof. ABA is equipped with different semantics for determining 'winning' sets of assumptions and -interchangeably and equivalently -'winning'sets of arguments. It is also equipped with a catalogue of computational techniques to determine whether given conclusions can be supported by a 'winning' set of arguments. These are in the form of disputes between (fictional) proponent and opponent players, provably correct w.r.t. the semantics. Albeit simple, ABA is powerful in that it can be used to represent and reason with a number of problems in AI and beyond: non-monotonic reasoning, preferences, decisions. While doing so, it encompasses the expressive and computational needs of these problems while affording the transparency and explanatory power of argumentation.

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Section: Aba Frameworksupporting

confidence: 76%

A tutorial on assumption-based argumentation

Toni

2014

Argument & Computation

134

137

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“…Most agent frameworks have an operational semantics, but no declarative semantics. Some logic-based frameworks like Golog, ALP agents and KGP [10] have a model-theoretic semantics, but represent the environment using time or state and manipulate the representation using the situation or event calculus. Metatem [6], on the other hand, is a logic-based agent language with a Kripke semantics for modal logic sentences resembling production rules.…”

Section: Related and Future Workmentioning

confidence: 99%

An Agent Language with Destructive Assignment and Model-Theoretic Semantics

Kowalski

Sadri

2010

Lecture Notes in Computer Science

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Abstract. In this paper we present an agent language that combines agent functionality with an action theory and model-theoretic semantics. The language is based on abductive logic programming (ALP), but employs a simplified state-free syntax, with an operational semantics that uses destructive assignment to manipulate a database, which represents the current state of the environment. The language builds upon the ALP combination of logic programs, to represent an agent's beliefs, and integrity constraints, to represent the agent's goals. Logic programs are used to define macro-actions, intensional predicates, and plans to reduce goals to sub-goals including actions. Integrity constraints are used to represent reactive rules, which are triggered by the current state of the database and recent agent actions and external events. The execution of actions and the assimilation of observations generate a sequence of database states. In the case of the successful solution of all goals, this sequence, taken as a whole, determines a model that makes the agent's goals and beliefs all true.

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“…A similar approach is known as KGP (Knowledge, Goals and Plans), which is based on logic programming with priorities, taking beliefs, desires and intentions as a starting point, but adding reasoning capabilities, state transitions and control -see [15]. Furthermore, it is implemented directly in computational logic.…”

Section: A Active Logic Programmingmentioning

confidence: 99%

Application of Hybrid Agents to Smart Energy Management of a Prosumer Node

Caianiello

Costantini

Gasperis

et al. 2013

Distributed Computing and Artificial Intelligence

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-We outline a solution to the problem of intelligent control of energy consumption of a smart building system by a prosumer planning agent that acts on the base of the knowledge of the system state and of a prediction of future states. Predictions are obtained by using a synthetic model of the system as obtained with a machine learning approach. We present case studies simulations implementing different instantiations of agents that control an air conditioner according to temperature set points dynamically chosen by the user. The agents are able of energy saving while trying to keep indoor temperature within a given comfort interval.

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Computational Logic Foundations of KGP Agents

Cited by 33 publications

References 50 publications

A tutorial on assumption-based argumentation

A tutorial on assumption-based argumentation

An Agent Language with Destructive Assignment and Model-Theoretic Semantics

Application of Hybrid Agents to Smart Energy Management of a Prosumer Node

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