Similarity based task timely termination method for image based intelligent agents.

Due to the hallucination of the underlying large language model(LLMs) or the unclear description of the task's ultimate goal, the agents have become somewhat confused. Despite having completed tasks, they have not ceased working, leading to a waste of resource. We propose similarity-based task timely termination method for image-based intelligent agents, This method involves recording the scenario state after the completion of each sub-task and comparing it with the fully completed task scenario state using a structural similarity method.

An optimization method for wireless sensor networks coverage based on genetic algorithm and reinforced whale algorithm.

In response to the problem of coverage redundancy and coverage holes caused by the random deployment of nodes in wireless sensor networks (WSN), a WSN coverage optimization method called GARWOA is proposed, which combines the genetic algorithm (GA) and reinforced whale optimization algorithm (RWOA) to balance global search and local development performance. First, the population is initialized using sine map and piecewise linear chaotic map (SPM) to distribute it more evenly in the search space. Secondly, a non-linear improvement is made to the linear control factor 'a' in the whale optimization algorithm (WOA) to enhance the efficiency of algorithm exploration and development.

Pursuit and Evasion Strategy of a Differential Game Based on Deep Reinforcement Learning.

Since the emergence of deep neural network (DNN), it has achieved excellent performance in various research areas. As the combination of DNN and reinforcement learning, deep reinforcement learning (DRL) becomes a new paradigm for solving differential game problems. In this study, we build up a reinforcement learning environment and apply relevant DRL methods to a specific bio-inspired differential game problem: the dog sheep game.

A linear programming computational framework integrates phosphor-proteomics and prior knowledge to predict drug efficacy.

Background: In recent years, the integration of 'omics' technologies, high performance computation, and mathematical modeling of biological processes marks that the systems biology has started to fundamentally impact the way of approaching drug discovery. The LINCS public data warehouse provides detailed information about cell responses with various genetic and environmental stressors. It can be greatly helpful in developing new drugs and therapeutics, as well as improving the situations of lacking effective drugs, drug resistance and relapse in cancer therapies, etc.