From the perspective of philosophy, the idea of humans lying to themselves seems irrational and maladaptive, if even possible. However, the paradigm of cognitive modularity admits the possibility of self-deception. Trivers argues that self-deception can increase fitness by improving the effectiveness of inter-personal deception. Ramachandran criticizes Trivers' conjecture, arguing that the costs of self-deception outweigh its benefits. We first modify a well-known cognitive modularity model of Minsky to formalize a cognitive model of self-deception. We then use Byrne's multi-dimensional dynamic character meta-model to integrate the cognitive model into an evolutionary hawk-dove game in order to investigate Trivers' and Ramachandran's conjectures. By mapping the influence of game circumstances into cognitive states, and mapping the influence of multiple cognitive modules into player decisions, our cognitive definition of self-deception is extended to a behavioral definition of self-deception. Our cognitive modules, referred to as the hunger and fear daemons, assess the benefits and the cost of competition and generate player beliefs. Daemon-assessment of encounter benefits and costs may lead to inter-daemonic conflict, that is, ambivalence, about whether or not to fight. Player-types vary in the manner by which such inter-daemonic conflict is resolved, and varieties of self-deception are modeled as type-specific conflict-resolution mechanisms. In the display phase of the game, players signal to one another and update their beliefs before finally committing to a decision (hawk or dove). Self-deception can affect player beliefs, and hence player actions, before or after signaling. In support of Trivers' conjecture, the self-deceiving types do outperform the non-self-deceiving type. We analyse the sensitivity of this result to parameters of the cognitive model, specifically the cognitive resolution of the players and the influence of player signals on co-player beliefs.
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Modeling and Simulation
- Biochemistry, Genetics and Molecular Biology(all)
- Immunology and Microbiology(all)
- Agricultural and Biological Sciences(all)
- Applied Mathematics