Vaporization and cracking of liquid oil injected in a gas–solid riser (fluid catalytic cracking
riser reactor) was computationally studied in this work. Evaporation of a single drop injected in …

Markov decision processes capture sequential decision making under uncertainty, where an
agent must choose actions so as to optimize long term reward. The paper studies efficient …

Imitation learning refers to the problem of learning how to behave by observing a teacher in
action. We consider imitation learning in relational domains, in which there is a varying …

We consider symbolic dynamic programming (SDP) for solving Markov Decision Processes (MDP)
with factored state and action spaces, where both states and actions are described by …

We present a new paradigm for planning by learning, where the planner is given a model of
the world and a small set of states of interest, but no indication of optimal actions in these …

First order decision diagrams (FODD) were recently introduced as a compact knowledge
representation expressing functions over relational structures. FODDs represent numerical …

Many tasks in AI require representation and manipulation of complex functions. First-Order
Decision Diagrams (FODD) are a compact knowledge representation expressing functions …

In the recent years, there has been a surge in the adoption of agile development model and
continuous integration (CI) in software development. Recent trends have reduced average …

Dynamic programming algorithms have been successfully applied to propositional stochastic
planning problems by using compact representations, in particular algebraic decision …

Dynamic programming algorithms have been successfully applied to propositional stochastic
planning problems by using compact representations, in particular algebraic decision …