Generality in artificial intelligence
Communications of the ACM
ACM Computing Surveys (CSUR)
Learning and exploiting context in agents
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 3
The Pragmatic Roots of Context
CONTEXT '99 Proceedings of the Second International and Interdisciplinary Conference on Modeling and Using Context
Simulating Context Effects in Problem Solving with AMBR
CONTEXT '01 Proceedings of the Third International and Interdisciplinary Conference on Modeling and Using Context
Epistemological Aspects of Computer Simulation in the Social Sciences
Integrating learning and inference in multi-agent systems using cognitive context
MABS'06 Proceedings of the 2006 international conference on Multi-agent-based simulation VII
Epistemological perspectives on simulation: overview and introduction
Computational & Mathematical Organization Theory
Environmental Modelling & Software
On Some Lessons from Modeling Contexts in Complex Problem Solving in Information Technology
Journal of Information Technology Research
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Context is everywhere in the human social and cognitive spheres but it is often implicit and unnoticed. However, when one is involved in trying to understand and model the social and cognitive realms context becomes an important factor. This paper is an analysis of the role and effects of context on social simulation and a call for it to be squarely faced by the social simulation community. It briefly looks at some different kinds of context, and discussed the difficulty of talking about context, before looking at the "context heuristic" that seems to be used in human cognition. This allows for rich and fuzzy context recognition to be combined with crisp `foreground' belief update and reasoning. Such a heuristic allows for causality to make sense, and limits the phenomena of causal spread--it is thus at the root of the modelling enterprise. This analysis is then applied to simulation modelling, considering the context of a simulation, and its ramifications, in particular, why generalisation is so hard.