Abstract
While most robots in human robot interaction scenarios take instructions from humans, the ideal would be that humans and robots collaborate with each other. The Defense Advanced Research Projects Agency Communicating with Computer program proposes the collaborative blocks world scenario as a testbed for this. This scenario requires the human and the computer to communicate through natural language to build structures out of toy blocks. To formulate and address this, we identify two main tasks. The first task, called the plan failure analysis, demands the robot to analyze the feasibility of a task and to determine the reasons(s) in case the task is not doable. The second task focuses on the ability of the robot to understand communications via natural language. We discuss potential solutions to both problems and present prototypical architecture for the integration of planning failure analysis and natural language communication into an intelligent agent architecture.
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- 1.
Fluents/actions with variables are shorthands for collections of their ground instantiations. The formalization used in this example is a variant of the block world domain representation in planning benchmarks and assumes that each block has a unique color. The goal is simplified to be “build a stack of two blue blocks.”
- 2.
Observe that the action \(ask\_permission(.)\) refers to a communication between the robot and the human user and thus is not included in the initial planning domain of \(\mathcal {P}_b\). Furthermore, we assume that the human is collaborative and thus would grant the robot the permission to use his blocks.
- 3.
If it cannot deal with a new word, the system should respond by asking for an alternative or about the meaning of the word.
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Baral, C., Son, T.C., Gelfond, M., Mitra, A. (2016). Plan Failure Analysis: Formalization and Application in Interactive Planning Through Natural Language Communication. In: Baldoni, M., Chopra, A., Son, T., Hirayama, K., Torroni, P. (eds) PRIMA 2016: Principles and Practice of Multi-Agent Systems. PRIMA 2016. Lecture Notes in Computer Science(), vol 9862. Springer, Cham. https://doi.org/10.1007/978-3-319-44832-9_25
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