Titlebook: Shepherding UxVs for Human-Swarm Teaming; An Artificial Intell Hussein A. Abbass,Robert A. Hunjet Book 2021 Springer Nature Switzerland AG

Myofibrils

乐器演奏者

Transparent Shepherding: A Rule-Based Learning Shepherd for Human Swarm Teamingm the challenges identified by the cognitive engineering community for building human autonomy teaming and how they scale to human swarm teaming. The discussion will follow with a description of rule-based machine learning with a focus on learning classifier systems as a representative for these alg

Corporeal

太空

opportune

Smart Shepherding: Towards Transparent Artificial Intelligence Enabled Human-Swarm Teams,s: what is shepherding and what makes shepherding an interesting problem? How does one design a smart shepherd for swarm guidance? What AI algorithms are required and how are they organised in a cognitive architecture to enable a smart shepherd? How does one design transparent AI for smart shepherding?

NAV

Cabg318

Simulating Single and Multiple Sheepdogs Guidance of a Sheep Swarmh basic swarm intelligence rules. Our simulation results show that synergising shepherds with swarming behaviours improves the effectiveness of the shepherds as measured by the speed of collecting and driving the sheep towards a target destination while maintaining a more compact and cohesive flock.

发芽

The Influence of Stall Distance on Effective Shepherding of a Swarmby setting the value for stall distance to an appropriate level in a herding model. A connection is made between the concept of stall distance for shepherds herding sheep agents in the model and real-world shepherds herding a group of sheep.

Allergic

Activity Recognition for Shepherdingthe perceived behaviour of an agent under observation from the perspective of an external observer. We present a method of classifying behaviour through the use of spatial data and codify action, behaviour, and intent states through a multi-level classification mapping process.

毗邻

Apprenticeship Bootstrapping Reinforcement Learning for Sky Shepherding of a Ground Swarm in Gazebosingle learning agent to influence and manage a larger swarm of rule-based entities. In this chapter, we present a learning algorithm for a sky shepherd-guiding rule-based AI-driven UGVs. The apprenticeship bootstrapping learning algorithm is introduced and is applied to the aerial shepherding task.