PSYC 213 Lecture Notes - Lecture 13: Ethnocentrism, Ingroups And Outgroups, Mutation Rate
3 Mar 2017
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Document Summary
Vtd conclusions stage progressions identity (non-normative: additive (non-normative, multiplicative static networks are either too powerful and miss additive stages too weak and fail to reach multiplicative stage illustrates how difficult it is to do simulations of cognitive conditions. Model give us insights as to why the develop these non-normative rules: always doing the best they can do with the computational resources they have. Ethnocentrism tendency to favor one"s own group conventional view cultural learning. New evidence: common throughout a diverse range of animal, may have a basis in biological evolution, cognition involved is simple (distinguish between in-group and out-group members and then behave accordingly. Agent-based models (abms) large number of interacting agents operating in an environment each agents behavior governed by rules triggered by their local condition rather than global information. High level summary descriptions emerge from the unfolding agent interactions. Von neumann neighborhood each agent interacts with each of its 4 immediate neighbors.
