Planning is vital to a wide range of domains, including robotics, military strategy, logistics, itinerary generation and more, that both humans and computers find difficult. Collaborative planning holds the promise of greatly improving performance on these tasks by leveraging the strengths of both humans and automated planners. However, this requires formalizing the problem domain and input, wh...

There has been a recent rise in research on real-time planning algorithms. Most of these algorithms address either the issue of response-time constraints or the issue of dynamic environments. We propose a new real-time planning algorithm, DYNORAII, to address both of these issues simultaneously. DYNORAII is structured as a sequence of ‘‘partial planning and execution’’ cycles to avoid obsolesce...

Numerous path planning solutions have been proposed to solve the navigation problem in static environments, potentially populated with dynamic obstacles. However, in dynamic environments, moving objects can be used to reach new locations. In this paper, we propose an online planning algorithm for unknown dynamic environments that focuses on accessibility and on the use of objects movements to r...

Planning deals with the problem of finding a partially ordered sequence of actions (plan) that transfers the world from some initial state to a desired state. Causal relations between actions play a critical role here. Introduction of explicit time and resources into planning is an important step towards modeling real-life problems. In this paper we propose a suboptimal domainindependent planni...

While universal plans tell a system how to reach a goal regardless of what state it is in, such plans are typically too large to represent. Hybrid systems execute plans where each action is implemented to robustly produce effects if the world does not stray outside the action’s control envelope. This paper presents a middle ground between these two extremes that uses plans, but also enables muc...

This article shows an extended work of [Kleinberg and Oren 2014]. It gives more properties of the graph time-inconsistency model raised in [Kleinberg and Oren 2014] by solving three open problems proposed in [Kleinberg and Oren 2014]. Generally speaking, it gives a tight upper bound for the ratio of actual cost due to time-inconsistency to minimum theoretic cost, and shows the hardness of motiv...

To react appropriately in hard real-time environments, a system must either employ fast dynamic planning or recall a pre-built reactive response. For complex problems, real-time, accurate dynamic planning may be impossible, and the complete set of possible reactions may be too large to build and store in advance. In this paper, we propose combining offiine and online planning such that a set of...

Time-inconsistency refers to a paradox in decision making where agents exhibit inconsistent behaviors over time. Examples are procrastination where agents tends to postpone easy tasks, and abandonments where agents start a plan and quit in the middle. These behaviors are undesirable in that agents make clearly suboptimal decisions over optimal ones. To capture such behaviors and more importantl...

The “planning as satisfiability” approach for classical planning establishes a correspondence between planning problems and logical theories, and, consequently, between plans and models. This work proposes a similar framework for contingency planning: considering contingent planning problems where the sources of indeterminism are incomplete knowledge about the initial state, non-inertial fluent...