Abstract: Systems and methods for simulating multi-agent within a virtual world in response to generated hypotheses are disclosed herein. The system can generate a virtual world that includes a set of agents. The system can receive instructions that include a question, including a first query and a first input item, and a set of input traits, which can be used to instantiate a set of agents. The system can generate a first hypothesis representing the first input item and can execute a first simulation session to generate a first output set. The system can generate a second data schema associated with a second hypothesis and execute a second simulation session to generate, using the second hypothesis and the first query, a second output set. Accordingly, the system can generate a sentiment summary and display the sentiment (impression) summary at a graphical user interface (GUI) accessible to an experimenter.

Abstract: A platform for adaptive multi-agent simulation in a virtual world instantiates a set of agents with input traits and executes a simulation session, generating an output set. Upon detecting a change event in the virtual world, a trained model recommends an evolution operation, which is applied to the set of agents to generate an evolved set. The evolution operation includes mutation, selection, crossover, deletion of agents, or a combination thereof. The platform persists at least a portion of the initial output set and executes a second simulation operation using the evolved agents, generating a new output set and thereby enabling analysis and comparison of simulation results. The disclosed adaptive simulation approach with persisted context enables realistic and dynamic modeling of complex systems.