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Found 9 papers, 2 papers with code
Where It Really Matters: Few-Shot Environmental Conservation Media Monitoring for Low-Resource Languages
Environmental conservation organizations routinely monitor news content on conservation in protected areas to maintain situational awareness of developments that can have an environmental impact.
NewsPanda: Media Monitoring for Timely Conservation Action
We introduce NewsPanda, a toolkit which automatically detects and analyzes online articles related to environmental conservation and infrastructure construction.
MAVIPER: Learning Decision Tree Policies for Interpretable Multi-Agent Reinforcement Learning
The first algorithm, IVIPER, extends VIPER, a recent method for single-agent interpretable RL, to the multi-agent setting.
Multi-agent Reinforcement Learning
reinforcement-learning
+1
Bandit Data-Driven Optimization
In this paper, we introduce bandit data-driven optimization, the first iterative prediction-prescription framework to address these pain points.
Artificial Intelligence for Social Good: A Survey
Artificial intelligence for social good (AI4SG) is a research theme that aims to use and advance artificial intelligence to address societal issues and improve the well-being of the world.
Learning and Planning in the Feature Deception Problem
In order to formally reason about deception, we introduce the feature deception problem (FDP), a domain-independent model and present a learning and planning framework for finding the optimal deception strategy, taking into account the adversary's preferences which are initially unknown to the defender.
Draining the Water Hole: Mitigating Social Engineering Attacks with CyberTWEAK
Cyber adversaries have increasingly leveraged social engineering attacks to breach large organizations and threaten the well-being of today's online users.
Deep Reinforcement Learning for Green Security Games with Real-Time Information
Green Security Games (GSGs) have been proposed and applied to optimize patrols conducted by law enforcement agencies in green security domains such as combating poaching, illegal logging and overfishing.
Designing the Game to Play: Optimizing Payoff Structure in Security Games
We study Stackelberg Security Games where the defender, in addition to allocating defensive resources to protect targets from the attacker, can strategically manipulate the attacker's payoff under budget constraints in weighted L^p-norm form regarding the amount of change.
