Exploring the advantages of using artificial agents to investigate animacy perception in cats and dogs

Animal-robot interaction-an emerging field at the intersection of biology and robotics

The field of animal-robot and organism-robot interaction systems (ARIS, ORIS) is a currently rapidly emerging field in biorobotics. In this special issue we aim for providing a comprehensive overview of the cutting-edge advancements and pioneering breakthroughs within this scientific and engineering discipline. Therefore, we collected scientific articles that delineate and expound upon the complexity of these remarkable biohybrid systems. These configurations stand as engineered conduits, facilitating the accurate investigation and profound exploration of the multifaceted interactions between robotic devices and biological entities, including various fish species, honeybees and plants. Also the human factor plays a role in this collection, as we also include a philosophical perspective on such systems as well as an augmented reality setup that brings humans into the loop with living fish. Within our editorial purview, we categorize the scientific contributions based on their focal points, differentiating between examinations of singular agent-to-agent interactions, extensions to the social stratum, and further expansions to the intricate levels of swarm dynamics, colonies, populations, and ecosystems. Considering potential applications, we delve into the multifaceted domains wherein these biohybrid systems might be applied. This discourse culminates in a tentative glimpse into the future trajectories these technologies might traverse, elucidating their promising prospects for both scientific advancement and societal enrichment. In sum, this special issue aims at facilitating the convergence of diverse insights, at encapsulating the richness of the ARIS and ORIS domain, and at charting a course toward the untapped prospects lying at the nexus of biology and robotics.

Dogs outperform cats both in their testability and relying on human pointing gestures: a comparative study

The dog is a so far unique species to study interspecific communication and a promising evolutionary model for preverbal human communication. Recently cats were reported to show some similar skills to dogs. Here we directly compared both the testability and the success of companion dogs and cats in relying on human distal pointing gestures. Due to differences in their domestication, social and ecological background, and developmental processes, we expected better performance from dogs compared to cats. Using an object-choice task, cats made considerably fewer choices than dogs in the laboratory environment, and their tendency to make a choice declined during trials. They were slightly more testable at home, where their willingness to choose did not decrease over time. Dogs made more successful choices than cats, both at the group and individual level, irrespective of the type of the pointing gesture. Older cats were more successful. Despite the two species' rather similar role nowadays as human companions, our results support previous findings suggesting that, compared to the dog, the cat is a less ideal model to study some human communicative abilities in a laboratory environment.

Identifying critical kinematic features of animate motion and contribution to animacy perception

Humans can distinguish flying birds from drones based solely on motion features when no image information is available. However, it remains unclear which motion features of animate motion induce our animacy perception. To address this, we first analyzed the differences in centroid motion between birds and drones, and discovered that birds exhibit greater acceleration, angular speed, and trajectory fluctuations. We further determined the order of their importance in evoking animacy perception was trajectory fluctuations, acceleration, and speed. More interestingly, people judge whether a moving object is alive using a feature-matching strategy, implying that animacy perception is induced in a key feature-triggered way rather than relying on the accumulation of evidence. Our findings not only shed light on the critical motion features that induce animacy perception and their relative contributions but also have important implications for developing target classification algorithms based on motion features.

After 150 years of watching: is there a need for synthetic ethology?

The Darwinian idea of mental continuity is about 150 years old. Although nobody has strongly denied this evolutionary link, both conceptually and practically, relative slow advance has been made by ethology and comparative psychology to quantify mental evolution. Debates on the mechanistic interpretation of cognition often struggle with the same old issues (e.g., associationism vs cognitivism), and in general, experimental methods have made also relative slow progress since the introduction of the puzzle box. In this paper, we illustrate the prevailing issues using examples on 'mental state attribution' and 'perspective taking" and argue that the situation could be improved by the introduction of novel methodological inventions and insights. We suggest that focusing on problem-solving skills and constructing artificial agents that aim to correspond and interact with biological ones, may help to understand the functioning of the mind. We urge the establishment of a novel approach, synthetic ethology, in which researchers take on a practical stance and construct artificial embodied minds relying of specific computational architectures the performance of which can be compared directly to biological agents.