As increasingly large-scale multiagent simulations are being implemented, new methods are becoming necessary for concisely summarizing the results of a simulation run. Here we pose this as the problem of simulation summarization: how to extract the causally-relevant states from the trajectories of the agents. We present a simple algorithm to compress agent trajectories through state space by id...

Pseudoreplication is the failure of a statistical analysis to properly incorporate the true structure of randomness present in the data. It has been well documented and studied in the ecological literature but has received little attention in the fisheries literature. Avoiding pseudoreplication in analyses of fisheries data can be difficult due to the complexity of the statistical procedures re...

We address the state space explosion problem inherent to model-checking timed systems with a large number of components. The main challenge is to obtain pertinent global timing constraints from the timings in the components alone. To this end, we make use of auxiliary clocks to automatically generate new invariants which capture the constraints induced by the synchronisations between components...

Kalman filtering has been widely considered for dynamic state estimation in smart grids. Despite its unique merits, the Kalman Filter (KF)-based dynamic state estimation can be undesirably influenced by cyber adversarial attacks that can potentially be launched against the communication links in the Cyber-Physical System (CPS). To enhance the security of KF-based state estimation, in this paper...

Sprayers are important tools in agriculture that usually moved on the field by tractor. Sprayers should distribute the constant rate of chemicals during various conditions encountered in the field. Unwanted vibrations of sprayer boom cause redaction of its life time and over doses and under doses of chemical sprayed on the field. Therefore, in this study a model of suspension system for rotatio...

In order to apply formal methods in practice, the practitioner has to comprehend a vast amount of research literature and realistically evaluate practical merits of different approaches. In this paper we focus on explicit finite state model checking and study this area from practitioner’s point of view. We provide a systematic overview of techniques for fighting state space explosion and we ana...

A class of nonhomogeneous Markov systems with hierarchic state space working in diierent scales of time (slow and fast) that are adequate mathematical models at the analysis and modelling of various classes of computing systems and networks of a complex stochastic structure is studied. Models of asymptotic decreasing dimension and enlargement (merging) of state space are considered. Application...

ion • Very successful in (non-probabilistic) model checking − essential for verification of large/infinite-state systems • Construct abstract model A of concrete model M − details not relevant to some property of interest removed − e.g. partition of state space based on a set of predicates • Non-probabilistic case: existential abstraction − conservative: existence of path in M implies existence...

Software model checking, as an undecidable problem, has three possible outcomes: (1) the program satisfies the specification, (2) the program does not satisfy the specification, and (3) the model checker fails. The third outcome usually manifests itself in a space-out, time-out, or one component of the verification tool giving up; in all of these failing cases, significant computation is perfor...

This paper presents a method by which a reinforcement learning agent can solve the incomplete perception problem using memory. The agent uses a hidden Markov model (HMM) to represent its internal state space and creates memory capacity by splitting states of the HMM. The key idea is a test to determine when and how a state should be split: the agent only splits a state when doing so will help t...