When: Friday, June 10, 2022, 10am (CEST).

Where: Zoom online, check the address in the Google Calendar Event.

Topic: Iterative Depth-First Search for Fully Observable Non-Deterministic Planning

Speaker: Dr. Ramon Fraga Pereira, Research Associate at the Dipartimento di Ingegneria Informatica, Automatica e Gestionale (DIAG) at Sapienza Università di Roma, working with Prof. Dr. Giuseppe De Giacomo on his Advanced ERC project WhiteMech.

Abstract

Fully Observable Non-Deterministic (FOND) planning models uncertainty through actions with non-deterministic effects. Existing FOND planning algorithms are effective and employ a wide range of techniques. However, most of the existing algorithms are not robust for dealing with both non-determinism and task size. In this paper, we develop a novel iterative depthfirst search algorithm that solves FOND planning tasks and produces strong cyclic policies. Our algorithm is explicitly designed for FOND planning, addressing more directly the non-deterministic aspect of FOND planning, and it also exploits the benefits of heuristic functions to make the algorithm more effective during the iterative searching process. We compare our proposed algorithm to well-known FOND planners, and show that it has robust performance over several distinct types of FOND domains considering different metrics.

Short Bio

Dr. Ramon Fraga Pereira is a Research Associate at the Dipartimento di Ingegneria Informatica, Automatica e Gestionale (DIAG) at Sapienza Università di Roma, working with Prof. Dr. Giuseppe De Giacomo on his Advanced ERC project WhiteMech. He obtained his Ph.D. degree in 2020, at Pontifical Catholic University of Rio Grande do Sul (PUCRS), Porto Alegre, Brazil, under the supervision of Prof. Dr. Felipe Meneguzzi (PUCRS) and Dr. Miquel Ramírez (University of Melbourne). During his Ph.D. (from June 2018 to April 2019) he was a Ph.D. Intern in the School of Computing and Information at the University of Melbourne, under the supervision of Dr. Miquel Ramírez.

In 2020, he was recognized as having the best Ph.D. thesis in Artificial Intelligence in Brazil, CTDIAC at 9th the Brazilian Conference on Intelligent Systems (BRACIS).

His research is in the field of Artificial Intelligence, particularly in the area of Automated Planning. Over the past years, he has been working on Goal and Plan Recognition techniques over several types of domain models.

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