Unifying study on human and web problem solving: A brain informatics perspective

Problem-solving is one of the most important capabilities of human intelligence and has been studied in cognitive science and AI, where it is addressed in conjunction with reasoning centric cognitive functions such as attention, control, heuristic search, reasoning, learning, and so on, using a logic based symbolic and/or connectionist approach. Logic based problem-solving may be viewed as theoretic models that are mathematical systems with no real time and memory constraints. Web-based problem- solving systems need real-time response and deal with global, multiple, ation sources. In order to develop a Web based problem-solving system with human-level capabilities, we need to better understand how human being does complex adaptive, distributed problem-solving and reasoning, as well as how intelligence evolves for individuals and societies, over time and place. Ignoring what goes on in human brain and focusing instead on behavior has been a large impediment to understanding complex human adaptive, distributed problem-solving and reasoning. Granular Computing can be viewed as a novel approach in computational intelligence focusing on simulating human thinking and problem solving at multiple levels of granularity. It results in a powerful viewpoint of understanding human thinking and problem solving in depth, which is perhaps more important than any of its specific and concrete methods. Furthermore, how to organize information sources is very important and the problem-solving and reason o the structure of information sources. In fact, the human brain can be regarded as a huge distributed knowledge base with multiple information granule networks. Why a people can give a reasonable answer within a reasonable time when he/she received a question (a reasoning problem)? Understanding principles and mechanisms of human information organization, retrieval and selection in depth aims to find more cognitively inspired methods of problem-solving and reasoning at a Web scale. In - - this talk, we describe studying on human and Web problem-solving and reasoning in a unified way from the viewpoint of Brain Informatics. The key question is "can we find a new cognitive model for developing human-level Web based network reasoning and problem-solving?" In order to answer this question, we investigate the cognitive mechanism and neural basis of human problem solving and reasoning, for developing new cognitively inspires. Based on the above results, we will implement problem solver markup language (PSML) for representing, organizing, retrieving, and selecting Web information sources with multiple levels of granularity, and develop PSML based Web inference engines for personalized wisdom Web problem solving and services.