Swarms can be rational.

The emergence of collective order in swarms from local, myopic interactions of their individual members is of interest to biology, sociology, psychology, computer science, robotics, physics and economics. , whose members unknowingly work towards a common goal, are particularly perplexing: members sometimes take individual actions that maximize collective utility, at the expense of their own. This seems to contradict expectations of individual rationality.

The visual stimuli attributes instrumental for collective-motion-related decision-making in locusts.

Visual interactions play an instrumental role in collective-motion-related decision-making. However, our understanding of the various tentative mechanisms that can serve the visual-based decision-making is limited. We investigated the role that different attributes of the visual stimuli play in the collective-motion-related motor response of locust nymphs.

Vision-based collective motion: A locust-inspired reductionist model.

Naturally occurring collective motion is a fascinating phenomenon in which swarming individuals aggregate and coordinate their motion. Many theoretical models of swarming assume idealized, perfect perceptual capabilities, and ignore the underlying perception processes, particularly for agents relying on visual perception. Specifically, biological vision in many swarming animals, such as locusts, utilizes monocular non-stereoscopic vision, which prevents perfect acquisition of distances and velocities.

The hybrid bio-robotic swarm as a powerful tool for collective motion research: a perspective.

Swarming or collective motion is ubiquitous in natural systems, and instrumental in many technological applications. Accordingly, research interest in this phenomenon is crossing discipline boundaries. A common major question is that of the intricate interactions between the individual, the group, and the environment.

Towards Computational Modeling of Human Goal Recognition.

Recently, we are seeing the emergence of plan- and goal-recognition algorithms which are based on the principle of . These avoid the use of a plan library that compactly encodes all possible observable plans, and instead generate plans dynamically to match the observations. However, recent experiments by Berkovitz (Berkovitz, The effect of spatial cognition and context on robot movement legibility in human-robot collaboration, 2018) show that in many cases, humans seem to have reached quick (correct) decisions when observing motions which were far from rational (optimal), while optimal motions were slower to be recognized.

Comparing Plan Recognition Algorithms Through Standard Plan Libraries.

Plan recognition deals with reasoning about the goals and execution process of an actor, given observations of its actions. It is one of the fundamental problems of AI, applicable to many domains, from user interfaces to cyber-security. Despite the prevalence of these approaches, they lack a standard representation, and have not been compared using a common testbed.

Molecular Robots Obeying Asimov's Three Laws of Robotics.

Asimov's three laws of robotics, which were shaped in the literary work of Isaac Asimov (1920-1992) and others, define a crucial code of behavior that fictional autonomous robots must obey as a condition for their integration into human society. While, general implementation of these laws in robots is widely considered impractical, limited-scope versions have been demonstrated and have proven useful in spurring scientific debate on aspects of safety and autonomy in robots and intelligent systems. In this work, we use Asimov's laws to examine these notions in molecular robots fabricated from DNA origami.