The AgentSpeak type of languages are considered for decision making in autonomous control systems. To reduce the complexity and increase the verifiability of decision making, a limited instruction set agent (LISA) is introduced. The new decision method is structurally simpler than its predecessors and easily lends itself to both design time and runtime verification methods. The process of conve...

In this paper we investigate the applicability of standard model checking approaches to verifying properties in probabilistic programming. As the operational model for a standard probabilistic program is a potentially infinite parametric Markov decision process, no direct adaption of existing techniques is possible. Therefore, we propose an on– the–fly approach where the operational model is su...

Previous research on the effects of probability and delay on decision-making has focused on examining each dimension separately, and hence little is known about when these dimensions are combined into a single choice option. Importantly, we know little about the psychological processes underlying choice behavior with rewards that are both delayed and probabilistic. Using a process-tracing exper...

A portfolio optimization problem on an infinite time horizon is considered. Risky asset price obeys a logarithmic Brownian motion, and the interest rate varies according to an ergodic Markov diffusion process. Moreover, the interest rate fluctuation is correlated with the risky asset price fluctuation. The goal is to choose optimal investment and consumption policies to maximize the infinite ho...

Space launch projects are extremely risky, and any equipment failure or human error may lead to disastrous consequences. Probabilistic risk assessment (PRA) is beneficial qualitative analysis of risk, but it has not been paid enough attention in for space systems (SLSs). Compared with most this field, paper proposes a framework based on Bayesian network (BN) fuzzy method, which suitable probabi...

Damage to various regions of the prefrontal cortex (PFC) impairs decision making involving evaluations about risks and rewards. However, the specific contributions that different PFC subregions make to risk-based decision making are unclear. We investigated the effects of reversible inactivation of 4 subregions of the rat PFC (prelimbic medial PFC, orbitofrontal cortex [OFC], anterior cingulate...

We introduce a new approach to probabilistic logic programming in which probabilities are defined over a set of possible worlds. More precisely, classical program clauses are extended by a subinterval of [0; 1℄ that describes a range for the conditional probability of the head of a clause given its body. We then analyze the complexity of selected probabilistic logic programming tasks. It turns ...

Probabilistic inference procedures are usually coded painstakingly from scratch, for each target model and each inference algorithm. We reduce this effort by generating inference procedures from models automatically. We make this code generation modular by decomposing inference algorithms into reusable program-toprogram transformations. These transformations perform exact inference as well as g...

The precise probability of a compound event (e.g. e1 _ e2; e1 ^ e2) depends upon the known relationships (e.g. independence, mutual exclusion, ignorance of any relationship, etc.) between the primitive events that constitute the compound event. To date, most research on probabilistic logic programming 20, 19, 22, 23, 24] has assumed that we are ignorant of the relationship between primitive eve...

Probabilistic language models are widely used in Information Retrieval (IR) to rank documents by the probability that they generate the query. However, the implementation of the probabilistic representations with programming languages that favor matrix calculations is challenging. In this paper, we utilize matrix representations to reformulate the probabilistic language models. The matrix repre...