Multi-Agent Reinforcement Learning (MARL) is an emerging subfield of artificial intelligence that investigates how multiple autonomous agents can learn collaboratively and competitively within an ...
This collection supports and amplifies research related to SDG 4: Quality Education. Generative AI is transforming the conventional dyadic teacher-student dynamic into a triadic framework centered ...
You might have seen headlines sounding the alarm about the safety of an emerging technology called agentic AI.
The biggest challenge to AI initiatives is the data they rely on. More powerful computing and higher-capacity storage at lower cost has created a flood of information, and not all of it is clean. It ...
What if you could design a system where multiple specialized agents work together seamlessly, each tackling a specific task with precision and efficiency? This isn’t just a futuristic vision—it’s the ...
In April 2025, Anthropic announced that it had introduced a new feature called 'Research' to its chat AI 'Claude,' which performs detailed research and analysis according to user instructions. Claude ...
In mission-critical environments—think disaster response, financial systems, or supply chain logistics—success hinges on the seamless collaboration of multiple agents, whether they’re humans, machines ...
Few technologies have been subject to as much hype, misrepresentation, and speculation as AI. Some people say it’s bigger than electricity, others say it’s massively overhyped. One simple metaphor I ...
Overview: Reinforcement learning in 2025 is more practical than ever, with Python libraries evolving to support real-world simulations, robotics, and deci ...
According to Nvidia’s 2025 State of AI in Financial Services report, one in four firms identify portfolio optimization as the single most ROI generative application of AI in Finance. In reality, ...
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