DATEM
Monitor health and status of critical systems with machine-learning technologies
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OUR CORE R&D / These systems range from individual
autonomous robotic platforms to large-scale, multi-agent systems
for information management, command & control
These systems range from individual autonomous robotic platforms to large-scale, multi-agent systems for information management, command & control
Optimizing actions and plans is a key feature of decision-support tools, especially when decision makers have multiple goals. At Charles River, we help our customers face the challenge of creating multi-step plans that adapt to the real world. We use a variety of algorithms, including genetic/evolutionary algorithms, market-based negotiation algorithms, neural networks, and ant-colony optimization, to develop tools for optimization and automated planning. By integrating these algorithms with our expertise in designing human-computer interfaces, we create solutions that not only generate effective and efficient plans but also help decision makers understand their options and the potential tradeoffs.
Monitor health and status of critical systems with machine-learning technologies
Onboard AI for uncrewed surface vehicles
A tool to prioritize data collection
Role and task-tailored interfaces for mission planning
A system that detects and prevents cybersecurity breaches in military ground vehicles
A rapid human-computer interaction prototyping tool
A system using heterogeneous crowds for complex analysis problems
Avoiding malice with linguistics-inspired exploit testing
A weather and climate forecasting tool for mission planning
A framework of crowdsourcing tools for formal software verification
A tactical decision aid to generate UAS mission plans
Decision-support tools for ISR collection management
Visualization and collaboration tools for emergency response
