Abstract
In this Chapter seven approaches are proposed to distinguish Sapient Agents (SAs) from the entire class of Intelligent Agents (IAs). These approaches, taken both from engineering and computer science, are proposed mostly in the context of IAs for engineering design, but the results should have more general implications. First, we propose a distinction with regard to knowledge representation and domain knowledge, depending on how much general and multi-level they are. Then we compare tactical decisions with global strategies, in the context of planning, exploration of new representations in engineering, and evolutionary computation. Finally, we show how an SA should be able to “understand” the dynamics of search/reasoning by identifying emerging patterns and attractors.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Arciszewski, T., Sauer, T. and Schum, D. (2003) Conceptual Design:Chaos-Based Approach. Journal of Intelligent and Fuzzy Systems,No. 13, IOS Press, 45–60.
Arciszewski, T., Michalski, R.S., and Wnek, J. (1995) ConstructiveInduction: the Key to Design Creativity Preprints of Computational Models of Creative Design. Third International Round-Table Conference, Heron Island, Australia, 397–426.
Baeck, T., Fogel, D.B., and Michalewicz, Z. (2000) EvolutionaryComputation: Advanced Algorithms and Operators. Institute of Physics, London.
Campbell, M. (1999) Knowledge discovery in deep blue. Communicationsof the ACM, vol. 42, No. 11.
De Jong, K. (2006) Evolutionary Computation: A Unified Approach. MIT Press.
Gero J. S. and Brazier F. M. T., (eds.) (2002) Agents in Design.Preprints of the First International Workshop on Agents in Design,University of Sydney.
Gero, J. (2000) Computational Models of Innovative and CreativeDesign Processes In: Arciszewski, T. (ed.) Technological Forecasting& Social Change, Special Issue: Innovation: The Key to Progress inTechnology and Society. Vol. 64, No. 2 & 3.
Kennedy, J. and Eberhart, R. C. (2001) Swarm Intelligence. Morgan Kaufmann Publishers.
Michalski, R.S. (1994) Inferential Theory of Learning: DevelopingFoundations for Multistrategy Learning, In: Machine Learning: A Multistrategy Approach. Volume IV, Morgan Kaufmann Publishers.
Richards, N., Moriarty, D. E. and Miikkulainen, R.(1998) Evolvingneural networks to play Go. Applied Intelligence, vol. 8,no. 1, 85–96.
Russell, S. J., and Norvig, P. (1995) Artificial Intelligence: A Modern Approach Prentice Hall, New Jersey.
Skolicki, Z., Arciszewski, T. (2003) Intelligent Agents in Design.Proceedings of ASME 2003 Design Engineering Technical Conferencesand Computers and Information in Engineering Conference.
Sowa, J.F. (2000) Knowledge Representation: Logical, Philosophicaland Computations Foundations. Brooks/Cole.
Tecuci, G. (1998) Building Intelligent Agents: An Apprenticeship Multistrategy Learning Theory, Methodology, Tool, and Case Studies.Academic Press.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag London Limited
About this chapter
Cite this chapter
Skolicki, Z., Arciszewski, T. (2008). Sapient Agents – Seven Approaches. In: Mayorga, R.V., Perlovsky, L.I. (eds) Toward Artificial Sapience. Springer, London. https://doi.org/10.1007/978-1-84628-999-6_8
Download citation
DOI: https://doi.org/10.1007/978-1-84628-999-6_8
Publisher Name: Springer, London
Print ISBN: 978-1-84628-998-9
Online ISBN: 978-1-84628-999-6
eBook Packages: Computer ScienceComputer Science (R0)