Prediction and causal reasoning in planning

Nonlinear planners are often touted as having an efficiency advantage over linear planners. The reason usually given is that nonlinear planners, unlike their linear counterparts, are not forced to make arbitrary commitments to the order in which actions are to be performed. This ability to delay commitment enables nonlinear planners to solve certain problems with far less effort than would be required of linear planners. Here, it is argued that this advantage is bought with a significant reduction in the ability of a nonlinear planner to accurately predict the consequences of actions. Unfortunately, the general problem of predicting the consequences of a partially ordered set of actions is intractable. In gaining the predictive power of linear planners, nonlinear planners sacrifice their efficiency advantage. There are, however, other advantages to nonlinear planning (e.g., the ability to reason about partial orders and incomplete information) that make it well worth the effort needed to extend nonlinear methods. A framework is supplied for causal inference that supports reasoning about partially ordered events and actions whose effects depend upon the context in which they are executed. As an alternative to a complete but potentially exponential-time algorithm, researchers provide a provably sound polynomial-time algorithm for predicting the consequences of partially ordered events

Temporal Data Modeling and Reasoning for Information Systems

Temporal knowledge representation and reasoning is a major research field in Artificial Intelligence, in Database Systems, and in Web and Semantic Web research. The ability to model and process time and calendar data is essential for many applications like appointment scheduling, planning, Web services, temporal and active database systems, adaptive Web applications, and mobile computing applications. This article aims at three complementary goals. First, to provide with a general background in temporal data modeling and reasoning approaches. Second, to serve as an orientation guide for further specific reading. Third, to point to new application fields and research perspectives on temporal knowledge representation and reasoning in the Web and Semantic Web

Actor Network Procedures as Psi-calculi for Security Ceremonies

The actor network procedures of Pavlovic and Meadows are a recent graphical formalism developed for describing security ceremonies and for reasoning about their security properties. The present work studies the relations of the actor network procedures (ANP) to the recent psi-calculi framework. Psi-calculi is a parametric formalism where calculi like spi- or applied-pi are found as instances. Psi-calculi are operational and largely non-graphical, but have strong foundation based on the theory of nominal sets and process algebras. One purpose of the present work is to give a semantics to ANP through psi-calculi. Another aim was to give a graphical language for a psi-calculus instance for security ceremonies. At the same time, this work provides more insight into the details of the ANPs formalization and the graphical representation.Comment: In Proceedings GraMSec 2014, arXiv:1404.163

Actor-network procedures: Modeling multi-factor authentication, device pairing, social interactions

As computation spreads from computers to networks of computers, and migrates into cyberspace, it ceases to be globally programmable, but it remains programmable indirectly: network computations cannot be controlled, but they can be steered by local constraints on network nodes. The tasks of "programming" global behaviors through local constraints belong to the area of security. The "program particles" that assure that a system of local interactions leads towards some desired global goals are called security protocols. As computation spreads beyond cyberspace, into physical and social spaces, new security tasks and problems arise. As networks are extended by physical sensors and controllers, including the humans, and interlaced with social networks, the engineering concepts and techniques of computer security blend with the social processes of security. These new connectors for computational and social software require a new "discipline of programming" of global behaviors through local constraints. Since the new discipline seems to be emerging from a combination of established models of security protocols with older methods of procedural programming, we use the name procedures for these new connectors, that generalize protocols. In the present paper we propose actor-networks as a formal model of computation in heterogenous networks of computers, humans and their devices; and we introduce Procedure Derivation Logic (PDL) as a framework for reasoning about security in actor-networks. On the way, we survey the guiding ideas of Protocol Derivation Logic (also PDL) that evolved through our work in security in last 10 years. Both formalisms are geared towards graphic reasoning and tool support. We illustrate their workings by analysing a popular form of two-factor authentication, and a multi-channel device pairing procedure, devised for this occasion.Comment: 32 pages, 12 figures, 3 tables; journal submission; extended references, added discussio

Structurally Tractable Uncertain Data

Many data management applications must deal with data which is uncertain, incomplete, or noisy. However, on existing uncertain data representations, we cannot tractably perform the important query evaluation tasks of determining query possibility, certainty, or probability: these problems are hard on arbitrary uncertain input instances. We thus ask whether we could restrict the structure of uncertain data so as to guarantee the tractability of exact query evaluation. We present our tractability results for tree and tree-like uncertain data, and a vision for probabilistic rule reasoning. We also study uncertainty about order, proposing a suitable representation, and study uncertain data conditioned by additional observations.Comment: 11 pages, 1 figure, 1 table. To appear in SIGMOD/PODS PhD Symposium 201