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About

The ability to model and represent the world around us in our heads is critical to human intelligence. Not only do we create a representation of the world visible to us, we make inferences from what we know to expand our knowledge to include hidden facts that must be true, or most likely true. We categorize the world around us into taxonomies, we reason about time and the effects of events and actions, we reason about what other people know and believe and about their intentions, to arrive at decisions in tune with our goals. If we are to build agents, be they robots or virtual agents, we will need to impart this ability to represent knowledge and reason with it to them too.

In the second summer school on Representation in Artificial Intelligence (RinAI-2019) we cover the foundations of knowledge representation and the logical foundations of reasoning needed by such autonomous and intelligent agents.

The aim of the summer school is to bring budding AI researchers up to date with this important aspect of building intelligent machines. The summer school will cover the following topics – First Order Logic, Event Calculus, Default Reasoning, Description Logic and Ontology, Epistemic Reasoning, Graphical Models, Cognition, and Causality.

The summer school is targeted at PhD students and young scientists starting work in AI. There are a limited number of seats, and applicants with a demonstrated interest in the area will be given preference. Selected participants will be provided accommodation and food. A few seats may be available for faculty and industry sponsored persons on payment.

Speakers

Sutanu Chakraborti
Indian Institute of Technology Madras
Sujata Ghosh
Indian Statistical Institute Chennai
Deepak Khemani
Indian Institute of Technology Madras
Raghava Mutharaju
Indraprastha Institute of Information Technology Delhi
Manikandan Narayanan
Indian Institute of Technology Madras
Baskaran Sankaranarayanan
Indian Institute of Technology Madras
Partha Talukdar
Indian Institute of Science, Bangalore

Schedule


Thursday June 06
09:00 - 09:15 Inauguration
09:15 - 10:45 Deepak Khemani First Order Logic, Soundness and Completeness, Representation
Tea
11:00 - 12:30 Deepak Khemani Unification, Forward Chaining, Backward Chaining
Lunch
14:30 - 16:30 Deepak Khemani Resolution Refutation Method, Horn Clause Logic and Prolog
Tea
Friday June 07
09:00 - 10:30 Deepak Khemani Logic based Semantics of Natural Language
Tea
11:00 - 12:30 Deepak Khemani Variations on Classical Logic: Event Calculus, Default Reasoning
Lunch
14:30 - 16:30 Raghava Mutharaju The Semantic Web and OWL
Tea
Saturday June 08
09:00 - 10:30 Baskaran S RDF Introduction
Tea
11:00 - 12:30 Baskaran S RDF Stores and Use Cases
Lunch
14:30 - 16:30 Baskaran S, Raghava Mutharaju Hands-on with SPARQL
Tea
Monday June 10
09:00 - 10:30 Baskaran S OWL: Introduction, Description Logics, OWL flavors, Tableau, Use Cases
Tea
11:00 - 12:30 Baskaran S Case Study from Ford
Lunch
14:30 - 16:30 Baskaran S, Raghava Mutharaju Ontology Hands-on
Tea
Tuesday June 11
09:00 - 10:30 Manikandan N Representation with Bayesian Networks (Factorization and Independence)
Tea
11:00 - 12:30 Manikandan N Inferences on Bayesian Networks (Variable elimination)
Lunch
14:30 - 16:30 Manikandan N Learning Bayesian Networks, Causality
Tea
Wednesday June 12
09:00 - 10:30 Sujata Ghosh Multiagent Systems and Epistemic Logics
Tea
11:00 - 12:30 Sujata Ghosh Reasoning with Epistemic Logics
Lunch
14:30 - 16:30 Sujata Ghosh, Shikha Singh Epistemic Puzzles, Deception
Tea
Thursday June 13
09:00 - 10:30 Partha Talukdar Knowledge Graphs, Learning from the Web
Tea
11:00 - 12:30 Sujata Ghosh Computational Cognitive Modelling - Empirical Studies
Lunch
14:30 - 16:30 Sutanu Chakraborti Memory and Cognition