![]() ![]() To evaluate our framework, we use a task where a mobile robot and a human cooperatively collect objects in an open space, illustrating the main features of our framework in a real-world task. Second, a communication module that uses natural language processing in order to parse all communication between the robot and the human. First, a decision-theoretic module that is responsible for all task-related decision making (task identification, teammate identification, and planning). Our framework comprises two main modules, addressing the two key challenges in the interaction between a robot acting as the ad hoc agent and human teammates. This paper will tap into this potential by proposing HOTSPOT, the first framework for ad hoc teamwork in human-robot teams. ![]() However, research in ad hoc teamwork is predominantly focused on agent-only teams, but not in agent-human teams, which we believe is an exciting research avenue and has enormous application potential in human-robot teams. As pointed out in the seminal work on mental cognition by Kenneth Craik in 1943, animals utilize internal models of their external reality and of possible actions at their disposal in order to evaluate various alternatives and conclude which one to utilize to react to new situations. Ad hoc teamwork is a research topic in multi-agent systems whereby an agent (the "ad hoc agent") must successfully collaborate with a set of unknown agents (the "teammates") without any prior coordination or communication protocol. Ad hoc teamwork is a research topic in multi-agent systems whereby an agent (the 'ad hoc agent') must successfully collaborate with a set of unknown agents (the 'teammates') without any prior coordination or communication protocol. Skip 1INTRODUCTION Section 1 INTRODUCTION. ![]()
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