Abstract: In this paper, Q-learning and Double Q-learning reinforcement learning algorithms were used to fine-tune sliding mode controller parameters to balance the Ball-and-Beam system. Each ...

So, you want to get better at Java coding? That’s awesome. The thing is, just watching videos or reading books only gets you so far. You really need to get your hands dirty and write some code.

In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment, generate a ...

So, you want to get better at Java coding, huh? It’s a pretty popular language, and honestly, getting some hands-on practice is the best way to really learn it. Luckily, there are a bunch of places ...

Abstract: Model-Driven Engineering (MDE) emphasizes models as primary artifacts to enhance abstraction and automation in software development. However, manually defining model transformation rules is ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Soroosh Khodami discusses why we aren't ready ...

Tuesday’s elections were, by most measures, a stinging failure for Republicans. Democrats won the gubernatorial races in Virginia and New Jersey. A democratic socialist was elected mayor of New York ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

In this tutorial, we explore how exploration strategies shape intelligent decision-making through agent-based problem solving. We build and train three agents, Q-Learning with epsilon-greedy ...

Accurately estimating the Q-function is a central challenge in offline reinforcement learning. However, existing approaches often rely on a single global Q-function, which struggles to capture the ...