An evolutionary model of personality traits related to cooperative behavior using a large language model.

This study aims to demonstrate that Large Language Models (LLMs) can empower research on the evolution of human behavior, based on evolutionary game theory, by using an evolutionary model positing that instructing LLMs with high-level psychological and cognitive character descriptions enables the simulation of human behavior choices in game-theoretical scenarios. As a first step towards this objective, this paper proposes an evolutionary model of personality traits related to cooperative behavior using a large language model. In the model, linguistic descriptions of personality traits related to cooperative behavior are used as genes.

Evolution of metamemory based on self-reference to own memory in artificial neural network with neuromodulation.

The ability of humans to self-monitor and control their memory processes is called metamemory and has been widely studied as a component of metacognition in cognitive psychology. Metamemory in non-human animals has also been investigated in recent years, although it had been regarded as a truly unique characteristic of human memory. We attempt to evolve artificial neural networks with neuromodulation, which have a metamemory function.

Evolution of Complex Niche-Constructing Behaviors and Ecological Inheritance of Adaptive Structures in a Physically Grounded Environment.

Niche construction is a process in which organisms modify the selection pressures on themselves and others through their ecological activities, and ecological inheritance is the consequence of niche construction inherited through generations. However, it is still unclear how such mutual interactions between robots or embodied agents and their physical environments can yield complex and divergent evolutionary processes or an open-ended evolution. Our purpose is to clarify what kind of complex and various niche-constructing behaviors evolve in a physically grounded environment under various conditions of ecological inheritance of constructed structures and spatial relationships.

An integrated model of gene-culture coevolution of language mediated by phenotypic plasticity.

In this paper, we propose an agent-based model for investigating possible scenarios of genetic and cultural language evolution based on an integrated gene-culture coevolutionary framework. We focused on the following problems: (1) how communicative ability can evolve directionally under positive frequency-dependent selection and (2) how much of the directional effect there is between language and biological evolution. In our evolutionary experiments and analysis, we discovered a coevolutionary scenario involving the biological evolution of phenotypic plasticity and a cyclic coevolutionary dynamic between genetic and cultural evolution that is mediated by phenotypic plasticity.

Artificial Metamorphosis: Evolutionary Design of Transforming, Soft-Bodied Robots.

We show how the concept of metamorphosis, together with a biologically inspired model of multicellular development, can be used to evolve soft-bodied robots that are adapted to two very different tasks, such as being able to move in an aquatic and in a terrestrial environment. Each evolved solution defines two pairs of morphologies and controllers, together with a process of transforming one pair into the other. Animats develop from a single cell and grow through cellular divisions and deaths until they reach an initial larval form adapted to a first environment.

Population and Evolutionary Dynamics based on Predator-Prey Relationships in a 3D Physical Simulation.

Recent studies have reported that population dynamics and evolutionary dynamics, occurring at different time scales, can be affected by each other. Our purpose is to explore the interaction between population and evolutionary dynamics using an artificial life approach based on a 3D physically simulated environment in the context of predator-prey and morphology-behavior coevolution. The morphologies and behaviors of virtual prey creatures are evolved using a genetic algorithm based on the predation interactions between predators and prey.

Concurrent Bursty Behavior of Social Sensors in Sporting Events.

The advent of social media expands our ability to transmit information and connect with others instantly, which enables us to behave as "social sensors." Here, we studied concurrent bursty behavior of Twitter users during major sporting events to determine their function as social sensors. We show that the degree of concurrent bursts in tweets (posts) and retweets (re-posts) works as a strong indicator of winning or losing a game.

Emergent dynamics of fairness in the spatial coevolution of proposer and responder species in the ultimatum game.

While spatially local interactions are ubiquitous between coevolving species sharing recourses (e.g., plant-insect interactions), their effects on such coevolution processes of strategies involving the share of a resource are still not clearly understood.

Emergence of a dynamic resource partitioning based on the coevolution of phenotypic plasticity in sympatric species.

This paper investigates the coevolutionary dynamics of the phenotypic plasticity in the context of overlap avoidance behaviors of shared niches in sympatric species. Especially, we consider whether and how a differentiation of phenotypic plasticity can emerge under the assumption that there are no initial asymmetric relationships among coevolving species. We construct a minimal model where several different species participate in a partitioning of their shared niches, and evolve their behavioral plasticity to avoid an overlap of their niche use.

A simple computational model of the evolution of a communicative trait and its phenotypic plasticity.

We consider a simple computational model of the evolution of a quantitative trait and its phenotypic plasticity based on directional and positive frequency-dependent selection in order to explore whether and how leaning might facilitate evolution under the dynamics that arise from communicative interactions among individuals. In the model, each individual expresses, at many different times in its lifetime, its real-valued trait depending on the probability distribution determined by its own genotypes. In communicative interactions between two individuals, the contribution of an interaction to the fitness is high when their trait values are close to each other as well as large, which represents the positive frequency-dependent and directional components of selection, respectively.

Heterochrony and artificial embryogeny: a method for analyzing artificial embryogenies based on developmental dynamics.

Artificial embryogenies are an extension to evolutionary algorithms, in which genotypes specify a process to grow phenotypes. This approach has become rather popular recently, with new kinds of embryogenies being increasingly reported in the literature. Nevertheless, it is still difficult to analyze and compare the available embryogenies, especially if they are based on very different paradigms.

Cyclic coevolution of cooperative behaviors and network structures.

This paper aims at understanding coevolutionary dynamics of cooperative behaviors and network structures of interactions. We constructed an evolutionary model in which each individual not only has a strategy for prisoner's dilemma to play with its neighboring members on the network, but also has a strategy for changing its neighboring structure of the network. By conducting evolutionary experiments with various settings of the payoff matrix, we found that the coevolutionary cycles of cooperative behaviors of individuals and their network structures repeatedly occurred when both the temptation to defect and the cost for playing a game were moderate.

The dynamic changes in roles of learning through the Baldwin effect.

The interaction between evolution and learning called the Baldwin effect is a two-step evolutionary scenario caused by the balances between benefit and cost of learning in general. However, little is known about the dynamic evolution of these balances in complex environments. Our purpose is to give a new insight into the benefit and cost of learning by focusing on the quantitative evolution of phenotypic plasticity under the assumption of epistatic interactions.

Interactions between learning and evolution: the outstanding strategy generated by the Baldwin effect.

The Baldwin effect is known as an possible interaction between learning and evolution, where individual lifetime learning can influence the course of evolution without using any Lamarckian mechanism. Our concern is to consider the Baldwin effect in dynamic environments, especially when there is no explicit optimal solution through generations and this solution depends only on interactions among agents. We adopted the iterated Prisoner's Dilemma as a dynamic environment, introduced phenotypic plasticity into its strategies, and conducted computational experiments, in which phenotypic plasticity is allowed to evolve.