Lévy movements and a slowly decaying memory allow efficient collective learning in groups of interacting foragers.

Many animal species benefit from spatial learning to adapt their foraging movements to the distribution of resources. Learning involves the collection, storage and retrieval of information, and depends on both the random search strategies employed and the memory capacities of the individual. For animals living in social groups, spatial learning can be further enhanced by information transfer among group members. However, how individual behavior affects the emergence of collective states of learning is still poorly understood. Here, with the help of a spatially explicit agent-based model where individuals transfer information to their peers, we analyze the effects on the use of resources of varying memory capacities in combination with different exploration strategies, such as ordinary random walks and Lévy flights. We find that individual Lévy displacements associated with a slow memory decay lead to a very rapid collective response, a high group cohesion and to an optimal exploitation of the best resource patches in static but complex environments, even when the interaction rate among individuals is low.

Proprioception in Action: A Matter of Ecological and Social Interaction.

The aim of this paper is to provide a theoretical and formal framework to understand how the proprioceptive and kinesthetic system learns about body position and possibilities for movement in ongoing action and interaction. Whereas most weak embodiment accounts of proprioception focus on positionalist descriptions or on its role as a source of parameters for internal motor control, we argue that these aspects are insufficient to understand how proprioception is integrated into an active organized system in continuous and dynamic interaction with the environment. Our strong embodiment thesis is that one of the main theoretical principles to understand proprioception, as a perceptual experience within concrete situations, is the coupling with kinesthesia and its relational constitution-self, ecological, and social. In our view, these aspects are underdeveloped in current accounts, and an enactive sensorimotor theory enriched with phenomenological descriptions may provide an alternative path toward explaining this skilled experience. Following O'Regan and Noë (2001) sensorimotor contingencies conceptualization, we introduce three distinct notions of proprioceptive kinesthetic-sensorimotor contingencies (PK-SMCs), which we describe conceptually and formally considering three varieties of perceptual experience in action: PK-SMCs-self, PK-SMCs-self-environment, and PK-SMC-self-other. As a proof of concept of our proposal, we developed a minimal PK model to discuss these elements in detail and show their explanatory value as important guides to understand the proprioceptive/kinesthetic system. Finally, we also highlight that there is an opportunity to develop enactive sensorimotor theory in new directions, creating a bridge between the varieties of experiences of oneself and learning skills.

Collective learning from individual experiences and information transfer during group foraging.

Living in groups brings benefits to many animals, such as protection against predators and an improved capacity for sensing and making decisions while searching for resources in uncertain environments. A body of studies has shown how collective behaviours within animal groups on the move can be useful for pooling information about the current state of the environment. The effects of interactions on collective motion have been mostly studied in models of agents with no memory. Thus, whether coordinated behaviours can emerge from individuals with memory and different foraging experiences is still poorly understood. By means of an agent-based model, we quantify how individual memory and information fluxes can contribute to improving the foraging success of a group in complex environments. In this context, we define collective learning as a coordinated change of behaviour within a group resulting from individual experiences and information transfer. We show that an initially scattered population of foragers visiting dispersed resources can gradually achieve cohesion and become selectively localized in space around the most salient resource sites. Coordination is lost when memory or information transfer among individuals is suppressed. The present modelling framework provides predictions for empirical studies of collective learning and could also find applications in swarm robotics and motivate new search algorithms based on reinforcement.

Localization Transition Induced by Learning in Random Searches.

We solve an adaptive search model where a random walker or Lévy flight stochastically resets to previously visited sites on a d-dimensional lattice containing one trapping site. Because of reinforcement, a phase transition occurs when the resetting rate crosses a threshold above which nondiffusive stationary states emerge, localized around the inhomogeneity. The threshold depends on the trapping strength and on the walker's return probability in the memoryless case. The transition belongs to the same class as the self-consistent theory of Anderson localization. These results show that similarly to many living organisms and unlike the well-studied Markovian walks, non-Markov movement processes can allow agents to learn about their environment and promise to bring adaptive solutions in search tasks.