Since their appearance, computer programs have embodied discipline and structured approaches and methodologies. Yet, to this day, equipping machines with imaginative and creative capabilities remains one of the most challenging and fascinating goals we pursue. Intelligent software agents can behave intelligently in well-defined scenarios, relying on Machine Learning (ML), symbolic reasoning, and the ability of their developers for tailoring smart behaviors to specific application domains. However, to forecast the evolution of all possible scenarios is unfeasible. Thus, intelligent agents should autonomously/creatively adapt to the world’s mutability. This paper investigates the meaning of imagination in the context of cognitive agents. In particular, it addresses techniques and approaches to let agents autonomously imagine/simulate their course of action and generate explanations supporting it, and formalizes thematic challenges. Accordingly, we investigate research areas including: (i) reasoning and automatic theorem proving to synthesize novel knowledge via inference; (ii) automatic planning and simulation, used to speculate over alternative courses of action; (iii) machine learning and data mining, exploited to induce new knowledge from experience; and (iv) biochemical coordination, which keeps imagination dynamic by continuously reorganizing it.

Towards Explainable Visionary Agents: License to Dare and Imagine / Giovanni Ciatto, Amro Najjar, Jean-Paul Calbimonte, Davide Calvaresi. - STAMPA. - 12688:(2021), pp. 139-157. (Intervento presentato al convegno 3rd International Workshop on Explainable, Transparent Autonomous Agents and Multi-Agent Systems (EXTRAAMAS 2021) tenutosi a Virtual Event nel 3–7 May 2021) [10.1007/978-3-030-82017-6_9].

Towards Explainable Visionary Agents: License to Dare and Imagine

Giovanni Ciatto;
2021

Abstract

Since their appearance, computer programs have embodied discipline and structured approaches and methodologies. Yet, to this day, equipping machines with imaginative and creative capabilities remains one of the most challenging and fascinating goals we pursue. Intelligent software agents can behave intelligently in well-defined scenarios, relying on Machine Learning (ML), symbolic reasoning, and the ability of their developers for tailoring smart behaviors to specific application domains. However, to forecast the evolution of all possible scenarios is unfeasible. Thus, intelligent agents should autonomously/creatively adapt to the world’s mutability. This paper investigates the meaning of imagination in the context of cognitive agents. In particular, it addresses techniques and approaches to let agents autonomously imagine/simulate their course of action and generate explanations supporting it, and formalizes thematic challenges. Accordingly, we investigate research areas including: (i) reasoning and automatic theorem proving to synthesize novel knowledge via inference; (ii) automatic planning and simulation, used to speculate over alternative courses of action; (iii) machine learning and data mining, exploited to induce new knowledge from experience; and (iv) biochemical coordination, which keeps imagination dynamic by continuously reorganizing it.
2021
Explainable and Transparent AI and Multi-Agent Systems
139
157
Towards Explainable Visionary Agents: License to Dare and Imagine / Giovanni Ciatto, Amro Najjar, Jean-Paul Calbimonte, Davide Calvaresi. - STAMPA. - 12688:(2021), pp. 139-157. (Intervento presentato al convegno 3rd International Workshop on Explainable, Transparent Autonomous Agents and Multi-Agent Systems (EXTRAAMAS 2021) tenutosi a Virtual Event nel 3–7 May 2021) [10.1007/978-3-030-82017-6_9].
Giovanni Ciatto, Amro Najjar, Jean-Paul Calbimonte, Davide Calvaresi
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/842452
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