Ravi Palla

AAAI Conference 2020 System Paper

DICR: AI Assisted, Adaptive Platform for Contract Review

• Dan G. Tecuci
• Ravi Palla
• Hamid R. Motahari Nezhad
• Nishchal Ahuja
• Alex Monteiro
• Tigran Ishkhanov
• Nigel Duffy

In the regular course of business, companies spend a lot of effort reading and interpreting documents, a highly manual process that involves tedious tasks, such as identifying dates and names or locating the presence or absence of certain clauses in a contract. Dealing with natural language is complex and further complicated by the fact that these documents come in various formats (scanned image, digital formats) and have different degrees of internal structure (spreadsheets, invoices, text documents). We present DICR, an end-to-end, modular, and trainable system that automates the mundane aspects of document review and allows humans to perform the validation. The system is able to speed up this work while increasing quality of information extracted, consistency, throughput, and decreasing time to decision. Extracted data can be fed into other downstream applications (from dashboards to Q&A and to report generation).

AAAI Conference 2012 Conference Paper

Reformulating Temporal Action Logics in Answer Set Programming

• Joohyung Lee
• Ravi Palla

Temporal Action Logics (TAL) is a class of temporal logics for reasoning about actions. We present a reformulation of TAL in Answer Set Programming (ASP), and discuss some synergies it brings. First, the reformulation provides a means to compute TAL using efficient answer set solvers. Second, TAL provides a structured high-level language for ASP (possibly with constraint solving). Third, the reformulation allows us to compute integration of TAL and ontologies using answer set solvers, and we illustrate its usefulness in the healthcare domain in the context of medical expert systems.

AAAI Conference 2010 Conference Paper

Situation Calculus as Answer Set Programming

• Joohyung Lee
• Ravi Palla

We show how the situation calculus can be reformulated in terms of the first-order stable model semantics. A further transformation into answer set programs allows us to use an answer set solver to perform propositional reasoning about the situation calculus. We also provide an answer set programming style encoding method for Reiter’s basic action theories, which tells us how the solution to the frame problem in answer set programming is related to the solution in the situation calculus.

IJCAI Conference 2009 Conference Paper

• Paolo Ferraris
• Joohyung Lee
• Vladimir Lifschitz
• Ravi Palla

Splitting a logic program allows us to reduce the task of computing its stable models to similar tasks for smaller programs. This idea is extended here to the general theory of stable models that replaces traditional logic programs by arbitrary firstorder sentences and distinguishes between intensional and extensional predicates. We discuss two kinds of splitting: a set of intensional predicates can be split into subsets, and a formula can be split into its conjunctive terms.

IJCAI Conference 2009 Conference Paper

• Tae-Won Kim
• Joohyung Lee
• Ravi Palla

Recently, Ferraris, Lee and Lifschitz presented a general definition of a stable model that is similar to the definition of circumscription, and can even be characterized in terms of circumscription. In this paper, we show the opposite direction, which is, how to turn circumscription into the general stable model semantics, and based on this, how to turn circumscriptive event calculus into answer set programs. The reformulation of the event calculus in answer set programming allows answer set solvers to be applied to event calculus reasoning, handling more expressive reasoning tasks than the current SAT-based approach. Our experiments also show clear computational advantages of the answer set programming approach.