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Joshua R. Nahum
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Proceedings Papers
. ecal2017, ECAL 2017, the Fourteenth European Conference on Artificial Life306-313, (September 4–8, 2017) 10.1162/isal_a_052
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Fitness landscapes are visual metaphors that appeal to our intuition for real-world landscapes to help us understand how populations evolve. The object inspiring the metaphor is better described as a networks composed of all possible genotypes, but they are frequently simplified to a surface where the fitness of each genotype is represented by elevation. Selection drives evolving populations to ascend the landscape until they are dominated by genotypes from which no further beneficial mutations are likely, known as a peak. However, by allowing for environmental change, former peaks can vanish, forcing populations to resume adapting. To explore how changing environments affect adaptation, we used the digital evolution platform, Avida, wherein we could manipulate the organisms’ environment as they are subject to natural evolutionary forces. We found that transient exposure to alternate environments frequently resulted in more fit genotypes. Negative-frequency-dependent environments, in particular, yielded strong fitness benefits after returning to the original environment. Furthermore, we explored how such environmental change could yield adaptive benefits via valley crossing and how such knowledge could be exploited in systems where improving the rate of adaption is beneficial.
Proceedings Papers
. alif2016, ALIFE 2016, the Fifteenth International Conference on the Synthesis and Simulation of Living Systems408-415, (July 4–6, 2016) 10.1162/978-0-262-33936-0-ch068
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Memory is an essential component of intelligence as it enables an individual to make informed decisions based on past experiences. In the context of biological systems, however, what selective conditions promote the evolution of memory? Given that reliable memory is likely to be associated with costs, how much is it actually worth in different contexts? We use a genetic algorithm to measure the evolutionary importance of memory in the context of the Iterated Prisoners Dilemma, a game in which players receive a short-term gain for defection, but may obtain greater long- term benefits with cooperation. However, cooperation requires trust; cooperating when an opponent defects is the worst possible outcome. Memory allows a player to recall an opponents previous actions to determine how trustworthy that opponent is. While a player can earn a high payout by defecting, it will likely lose the trust of an opponent with memory, yielding a lower long-term payout. We determined the value of memory in the Iterated Prisoners Dilemma under various conditions. When memory is costly, players reduce their available memory and use short-term greedy strategies, such as Always Defect. Alternatively, when memory is inexpensive, players use well-known cooperative strategies, such as Tit-for-Tat. Our findings indicate that organisms playing against a static opponent evolve memory as expected. However, memory is much more challenging to evolve in coevolutionary scenarios where its value is uneven.