Neural-guided Ant Colony Optimization (ACO) currently suffers from a fundamental training-inference misalignment: policies are typically trained to generate static priors (e.g., heatmaps) from ...

Our Computer Science Ph.D. students are innovators, problem-solvers, and future leaders in the field. From pioneering research in AI and cybersecurity to breakthroughs in data science and HCI, they’re ...

In response to the shortcomings of the Salp Swarm Algorithm (SSA) such as low convergence accuracy and slow convergence speed, a Multi-Strategy-Driven Salp Swarm Algorithm (MSD-SSA) was proposed.

In the last 20 years, fragment-based drug discovery (FBDD) has become a popular and consolidated approach within the drug discovery pipeline, due to its ability to bring several drug candidates to ...

Predicting the stability of granular materials under particle removal has wide-reaching applications, including automating tunnel excavations. Searching for general laws that govern granular stability ...

In this paper, we introduce an active inference model of ant colony foraging behavior, and implement the model in a series of in silico experiments. Active inference is a multiscale approach to ...

//given some nodes, and some locations... test_nodes = {0: (0, 7), 1: (3, 9), 2: (12, 4), 3: (14, 11), 4: (8, 11) 5: (15, 6), 6: (6, 15), 7: (15, 9), 8: (12, 10), 9 ...