scholarly journals Model Checking Probabilistic Epistemic Logic for Probabilistic Multiagent Systems

2018 ◽  
Author(s):  
Chen Fu ◽  
Andrea Turrini ◽  
Xiaowei Huang ◽  
Lei Song ◽  
Yuan Feng ◽  
...  
Keyword(s):  
Linear Programming ◽  
Model Checking ◽  
Multiagent Systems ◽  
Epistemic Logic ◽  
Mixed Integer ◽  
Model Checker ◽  
Non Linear Programming ◽  
Smt Solver ◽  
Realistic Assumption ◽  
Novel Algorithm

In this work we study the model checking problem for probabilistic multiagent systems with respect to the probabilistic epistemic logic PETL, which can specify both temporal and epistemic properties. We show that under the realistic assumption of uniform schedulers, i.e., the choice of every agent depends only on its observation history, PETL model checking is undecidable. By restricting the class of schedulers to be memoryless schedulers, we show that the problem becomes decidable. More importantly, we design a novel algorithm which reduces the model checking problem into a mixed integer non-linear programming problem, which can then be solved by using an SMT solver. The algorithm has been implemented in an existing model checker and experiments are conducted on examples from the IPPC competitions.

scholarly journals Model Checking Temporal Epistemic Logic under Bounded Recall

2020 ◽  
Vol 34 (05) ◽  
pp. 7071-7078
Author(s):  
Francesco Belardinelli ◽  
Alessio Lomuscio ◽  
Emily Yu
Keyword(s):  
Model Checking ◽  
Incomplete Information ◽  
Epistemic Logic ◽  
Upper Bounds ◽  
Experimental Results ◽  
Model Checker ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Multi Agent ◽  
Bounded Recall

We study the problem of verifying multi-agent systems under the assumption of bounded recall. We introduce the logic CTLKBR, a bounded-recall variant of the temporal-epistemic logic CTLK. We define and study the model checking problem against CTLK specifications under incomplete information and bounded recall and present complexity upper bounds. We present an extension of the BDD-based model checker MCMAS implementing model checking under bounded recall semantics and discuss the experimental results obtained.

scholarly journals Security Constrained Unit Commitment in a Power System based on Benders Decomposition and Mixed Integer Non-linear Programming

2018 ◽  
Vol 7 (2.6) ◽  
pp. 283 ◽  
Author(s):  
Pranda Prasanta Gupta ◽  
Prerna Jain ◽  
Suman Sharma ◽  
Rohit Bhakar
Keyword(s):  
Linear Programming ◽  
Network Security ◽  
Power System ◽  
Optimal Power Flow ◽  
Benders Decomposition ◽  
Optimal Solution ◽  
Mixed Integer ◽  
Reserve Requirement ◽  
Non Linear Programming ◽  
Non Linear

In deregulated power markets, Independent System Operators (ISOs) maintains adequate reserve requirement in order to respond to generation and system security constraints. In order to estimate accurate reserve requirement and handling non-linearity and non-convexity of the problem, an efficient computational framework is required. In addition, ISO executes SCUC in order to reach the consistent operation. In this paper, a novel type of application which is Benders decomposition (BD) and Mixed integer non linear programming (MINLP) can be used to assess network security constraints by using AC optimal power flow (ACOPF) in a power system. It performs ACOPF in network security check evaluation with line outage contingency. The process of solving modified system would be close to optimal solution, the gap between the close to optimal and optimal solution is expected to determine whether a close to optimal solutionis accepetable for convenientpurpose. This approach drastically betters the fast computational requirement in practical power system .The numerical case studies are investigated in detail using an IEEE 118-bus system. 

A Review of Optimal Scheduling Cleaning of Refinery Crude Preheat Trains Subject to Fouling and Ageing

2011 ◽  
Vol 148-149 ◽  
pp. 643-651 ◽  
Author(s):  
Abdullatif Lacina Diaby ◽  
Lee Luong ◽  
Amer Yousef ◽  
Jonas Addai Mensah
Keyword(s):  
Artificial Intelligence ◽  
Linear Programming ◽  
Mixed Integer Linear Programming ◽  
Optimal Scheduling ◽  
Mixed Integer ◽  
Non Linear Programming ◽  
Efficient Performance ◽  
The Subject ◽  
Minlp Models ◽  
Optimisation Techniques

Refinery crude preheat train (CPHT) is prone to fouling and ageing effects due to the complexity of processed crude feedstock preheated prior to distillation. This has serious implications on the thermal and hydraulic performance of the CPHT. As a result, efficient performance of crude preheat trains is compromised and as such, optimal scheduling cleaning operations are required to restore performance. In this paper, we attempt to review the subject of fouling/ageing control and mitigation in crude preheat train network by optimal scheduling cleaning approach. Three prominent optimisation techniques/models namely Mathematical Models (Mixed integer linear programming (MILP) and Mixed integer non-linear programming (MINLP) models); Artificial Intelligence (AI) Models; and Heuristic Techniques used for achieving optimal cleaning are outlined.

Mixed Integer Non-Linear Programming models for Green Network Design

2013 ◽  
Vol 40 (1) ◽  
pp. 273-281 ◽  
Author(s):  
Rosario G. Garroppo ◽  
Stefano Giordano ◽  
Gianfranco Nencioni ◽  
Maria Grazia Scutellà
Keyword(s):  
Linear Programming ◽  
Network Design ◽  
Programming Models ◽  
Mixed Integer ◽  
Non Linear Programming ◽  
Non Linear
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