Multi-agent blackboard architecture for supporting legal decision making

Our research objective is to design a system to support legal decision-making using the multi-agent blackboard architecture. Agents represent experts that may apply various knowledge processing algorithms and knowledge sources. Experts cooperate with each other using blackboard to store facts about current case. Knowledge is represented as a set of rules. Inference process is based on bottom-up control (forward chaining). The goal of our system is to find rationales for arguments supporting different decisions for a given case using precedents and statutory knowledge. Our system also uses top-down knowledge from statutes and precedents to interactively query the user for additional facts, when such facts could affect the judgment. The rationales for various judgments are presented to the user, who may choose the most appropriate one. We present two example scenarios in Polish traffic law to illustrate the features of our system. Based on these results, we argue that the blackboard architecture provides an effecive approach to model situations where a multitude of possibly conflicting factors must be taken into account in decision making. We briefly discuss two such scenarios: incorporating moral and ethical factors in decision making by autonomous systems (e.g. self-driven cars), and integrating eudaimonic (well-being) factors in modeling mobility patterns in a smart city

On the role of computers in creativity-support systems

We report here on our experiences with designing computer-based creativity-support systems over several years. In particular, we present the design of three different systems incorporating different mechanisms of creativity. One of them uses an idea proposed by Rodari to stimulate imagination of the children in writing a picture-based story. The second one is aimed to model creativity in legal reasoning, and the third one uses low-level perceptual similarities to stimulate creation of novel conceptual associations in unrelated pictures.We discuss lessons learnt from these approaches, and address their implications for the question of how far creativity can be tamed by algorithmic approaches

On the role of metaphor in creative cognition

Abstract. We consider some examples of creativity in a number of diverse cognitive domains like art, science, mathematics, product development, legal reasoning, etc. to articulate an operational account of creative cognition. We present a model of cognition that explains how metaphor creates new insights into an object or a situation. The model is based on assuming that cognition invariably leads to a loss of information and that metaphor can recover some of this lost information. In this model we also contrast the role of traditional analogy (mapping based on existing conceptualization) with the role of metaphor (destroying existing conceptualizations in order to create new conceptualizations)