Rescue robots are expected to carry out reconnaissance and dexterity operations in
unknown environments comprising unstructured obstacles. Although a wide variety of …

Contemporary swarm indicators are often used in isolation, focussed on extracting
information at the individual or collective levels. Consequently, these are seldom integrated …

Effective coordination and cooperation among agents are crucial for accomplishing
individual or shared objectives in multi-agent systems. In many real-world multiagent …

For recognizing speakers in video streams, significant research studies have been made to
obtain a rich machine learning model by extracting high-level speaker's features such as …

We present a novel perspective on how connected vehicles can reduce total vehicular delay
arising due to the capacity drop phenomenon observed at fixed freeway bottlenecks. We …

Inferring the size of a collective from the motion of a few accessible units is a fundamental
problem in network science and interdisciplinary physics. Here, we recognize stochasticity …

In this work, we integratesocial'interactions into the MARL setup through a user-defined
relational network and examine the effects of agent-agent relations on the rise of emergent …

The aim of this work is to present a hybrid pedestrian model that describes the bidirectional
walking of crowds in a corridor. The self-propelled hard disk model combines both …

The hunter‐and‐gatherer approach copes with the problem of dynamic multirobot task
allocation, where tasks are unknowingly distributed over an environment. This approach …

Cooperative multi-agent reinforcement learning (MARL) approaches tackle the challenge of
finding effective multi-agent cooperation strategies for accomplishing individual or shared …