Social Cognitive Optimization (SCO)
[Chinese version]


Social Cognitive Optimization (SCO) is a simple optimization model based on the obseravational learning in human social cognition. The foundational entity for simulating human cognition is social cognitive (SC) agent. Each SC agent includes a memory (MD) and a set of action rules. Specially, the agent acquires social sharing information (called I) not only from the MD of other agents, but also from the medium, called library (L), which stores NL points.

Related Papers

  • Xiao-Feng Xie, Wen-Jun Zhang. Solving engineering design problems by social cognitive optimization. Genetic and Evolutionary Computation Conference (GECCO), LNCS 3102, Washington, USA, 2004: 261-262 [Extended PDF]
  • Xiao-Feng Xie, Wen-Jun Zhang, Zhi-Lian Yang. Social cognitive optimization for nonlinear programming problems. International Conference on Machine Learning and Cybernetics (ICMLC). Beijing, China, 2002: 779-783
  • Software Download
    name type* description
    SCO_NOP SRC (JAVA) social cognitive optimizer (SCO) for constrained numerical optimization
    *abbreviations: SRC=source code; BIN=binary code
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