In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.

Q: A perfectly rational decision-maker chooses the best action with the highest utility gain from a set of possible actions. The optimality principles that describe such decision processes do not take into account the computational costs of finding the optimal action. Bounded rational decision-making addresses this problem by specifically trading off information-processing costs and expected utility. Interestingly, a similar trade-off between energy and entropy arises when describing changes in thermodynamic systems. This similarity has been recently used to describe bounded rational agents. Crucially, this framework assumes that the environment does not change while the decision-maker is computing the optimal policy. When this requirement is not fulfilled, the decision-maker will suffer inefficiencies in utility, that arise because the current policy is optimal for an environment in the past. Here we borrow concepts from non-equilibrium thermodynamics to quantify these inefficiencies and illustrate with simulations its relationship with computational resources.

A: Bounded Rational Decision-Making in Changing Environments
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Q: Multi Expression Programming (MEP) is an evolutionary technique that may be used for solving computationally difficult problems. MEP uses a linear solution representation. Each MEP individual is a string encoding complex expressions (computer programs). A MEP individual may encode multiple solutions of the current problem. In this paper MEP is used for evolving a Traveling Salesman Problem (TSP) heuristic for graphs satisfying triangle inequality. Evolved MEP heuristic is compared with Nearest Neighbor Heuristic (NN) and Minimum Spanning Tree Heuristic (MST) on some difficult problems in TSPLIB. For most of the considered problems the evolved MEP heuristic outperforms NN and MST. The obtained algorithm was tested against some problems in TSPLIB. The results emphasizes that evolved MEP heuristic is a powerful tool for solving difficult TSP instances.

A: Evolving TSP heuristics using Multi Expression Programming
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Q: <lb>We endow prioritised default logic (PDL) with argumentation semantics<lb>using the ASPIC framework for structured argumentation, and prove<lb>that the conclusions of the justified arguments are exactly the prioritised<lb>default extensions. Argumentation semantics for PDL will allow for the<lb>application of argument game proof theories to the process of inference<lb>in PDL, making the reasons for accepting a conclusion transparent and<lb>the inference process more intuitive. This also opens up the possibility for<lb>argumentation-based distributed reasoning and communication amongst<lb>agents with PDL representations of mental attitudes.

A:
Argumentation Semantics for Prioritised Default Logic
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