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.Comment: PREVIOUSLY Mr. Jones -- Towards a Proactive Smart Room Orchestrator (appeared in AAAI 2017 Fall Symposium on Human-Agent Groups

A Cognitive Assistant for Visualizing and Analyzing Exoplanets

We demonstrate an embodied cognitive agent that helps scientists visualize and analyze exo-planets and their host stars. The prototype is situated in a room equipped with a large display, microphones, cameras, speakers, and pointing devices. Users communicate with the agent via speech, gestures, and combinations thereof, and it responds by displaying content and generating synthesized speech. Extensive use of context facilitates natural interaction with the agent

The impact of COVID-19 on flight networks

As COVID-19 transmissions spread worldwide, governments have announced and enforced travel restrictions to prevent further infections. Such restrictions have a direct effect on the volume of international flights among these countries, resulting in extensive social and economic costs. To better understand the situation in a quantitative manner, we analyzed the OpenSky Network data to clarify flight patterns and flight densities around the world. Then we observed relationships between flight numbers with new infection cases and the economy (the unemployment rate) in Barcelona. We found that the number of daily flights gradually decreased and then suddenly dropped 64% during the second half of March in 2020 after the United States and Europe enacted travel restrictions. We also observed a 51% decrease in the global flight network density decreased during this period. Regarding new COVID-19 cases, the United States had an unexpected surge regardless of travel restrictions. Finally, the layoffs for temporary workers in the tourism and airplane business increased by 4.3 fold in the weeks following Spain’s decision to close its borders.Peer ReviewedPostprint (published version