In this paper we present a method for systematically defining the process architecture of any organization. We begin by presenting a detailed interpretation of the upper levels of Zachman’s framework, providing an answer to the cell formed by the intersection of the perspective of the Planner (row 1) and the dimension of Function (column 2). Our method consists of four steps: capturing the orga...

Many refinements of Nash equilibrium yield solution correspondences which do not have closed graph in the space of payoffs or information. This has significance for implementation theory, especially under complete information. If a planner is concerned that all equilibria of his mechanism yield a desired outcome, and entertains the possibility that players may have even the slightest uncertaint...

In this paper we introduce a novel algorithm for incorporating uncertainty into lookahead planning. Our algorithm searches through connected graphs with uncertain edge costs represented by known probability distributions. As a robot moves through the graph, the true edge costs of adjacent edges are revealed to the planner prior to traversal. This locally revealed information allows the planner ...

A ne-motion planning technique is described for assemblies with narrow insertion clearances. A ne-motion planner receives as input a nominal assembly motion plan, computed from kinematic constraints alone. As described in a companion paper [4], the planner constructs an adjacency graph for each local contact space surrounding a problematic con guration in the nominal trajectory. A heuristic sea...

We propose a model of discrete time dynamic congestion games with atomic players and a single source-destination pair. The latencies of edges are composed by free-flow transit times and possible queuing time due to capacity constraints. We give a precise description of the dynamics induced by the individual strategies of players and of the corresponding costs, either when the traffic is control...

Agents operating in the real world often have to act under the conditions where time is critical: there is a limit on the time they can afford to spend on deliberating what action to execute next. Planners used by such agents must produce the best plans they can find within the amount of time available. The strategy of always searching for an optimal plan becomes infeasible in these scenarios. ...

Temporal planning (TP) is notoriously difficult because it requires to solve a propositional STRIPS planning problem with temporal constraints. In this paper, we propose an efficient strategy for solving TP, which combines, in an innovative way, several well established and studied techniques in AI, OR and constraint programming. Our approach integrates graph planning (a well studied planning p...

The problem of formulating plans under uncertainty and coping with dynamic decision problems is a major task of both artificial intelligence and control theory applications in medicine. In this paper we will describe a software package, called DT-Planner, designed to represent and solve dynamic decision problems that can be modelled as Markov decision processes, by exploiting a novel graphical ...

We propose two new methods for performing local path search directly in the image space of a camera sensor. The first technique utilizes a high-resolution local image space subsystem to determine the farthest point along a global Cartesian path that can be reached along an unobstructed heading, thereby short-cutting as much of the global path as possible. To the best of our knowledge, this is t...