Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Visualizations for an Explainable Planning Agent   In this paper, we report on the visualization capabilities of an Explainable
AI Planning (XAIP) agent that can support human in the loop decision making.
Imposing transparency and explainability requirements on such agents is
especially important in order to establish trust and common ground with the
end-to-end automated planning system. Visualizing the agent's internal
decision-making processes is a crucial step towards achieving this. This may
include externalizing the "brain" of the agent -- starting from its sensory
inputs, to progressively higher order decisions made by it in order to drive
its planning components. We also show how the planner can bootstrap on the
latest techniques in explainable planning to cast plan visualization as a plan
explanation problem, and thus provide concise model-based visualization of its
plans. We demonstrate these functionalities in the context of the automated
planning components of a smart assistant in an instrumented meeting space.

10
The categories of this paper are: q-bio
0
The categories of this paper are: hep-ph
5
The categories of this paper are: gr-qc
30
The categories of this paper are: q-alg
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The categories of this paper are: dg-ga
20
The categories of this paper are: acc-phys
16
The categories of this paper are: stat
29
The categories of this paper are: funct-an
15
The categories of this paper are: nucl-ex
25
The categories of this paper are: patt-sol
3
The categories of this paper are: physics
12
The categories of this paper are: nucl-th
34
The categories of this paper are: chem-ph
28
The categories of this paper are: alg-geom
18
The categories of this paper are: econ
13
The categories of this paper are: quant-ph