AI/ML Techniques

Why do Policy Gradient Methods work so well in Cooperative MARL? Evidence from Policy Representation

In cooperative multi-agent reinforcement learning (MARL), due to its on-policy nature, policy gradient (PG) methods are typically believed to be…

2 years ago

FIGS: Attaining XGBoost-level performance with the interpretability and speed of CART

FIGS (Fast Interpretable Greedy-tree Sums): A method for building interpretable models by simultaneously growing an ensemble of decision trees in…

2 years ago

The Berkeley Crossword Solver

We recently published the Berkeley Crossword Solver (BCS), the current state of the art for solving American-style crossword puzzles. The…

2 years ago

Rethinking Human-in-the-Loop for Artificial Augmented Intelligence

Figure 1: In real-world applications, we think there exist a human-machine loop where humans and machines are mutually augmenting each…

2 years ago

Best Practices for Building the AI Development Platform in Government

By John P. Desmond, AI Trends Editor  The AI stack defined by Carnegie Mellon University is fundamental to the approach…

2 years ago

Advance Trustworthy AI and ML, and Identify Best Practices for Scaling AI

By John P. Desmond, AI Trends Editor   Advancing trustworthy AI and machine learning to mitigate agency risk is a priority…

2 years ago

Promise and Perils of Using AI for Hiring: Guard Against Data Bias

By AI Trends Staff   While AI in hiring is now widely used for writing job descriptions, screening candidates, and automating interviews,…

2 years ago

Predictive Maintenance Proving Out as Successful AI Use Case

By John P. Desmond, AI Trends Editor   More companies are successfully exploiting predictive maintenance systems that combine AI and IoT…

2 years ago

Novelty In The Game Of Go Provides Bright Insights For AI And Autonomous Vehicles

By Lance Eliot, the AI Trends Insider   We already expect that humans to exhibit flashes of brilliance. It might not happen all…

2 years ago