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2. Devin AI - Wikipedia

   en.wikipedia.org/wiki/Devin_AI

   [4] [5] Compared to the GitHub Copilot tool, [3] [4] the software can code, debug, plan and problem solve via machine learning techniques. [5] Devin AI works through a user prompting the software with a task in natural language, with the software responding by showing its plan while implementing the code. [3]

3. Automated planning and scheduling - Wikipedia

   en.wikipedia.org/wiki/Automated_planning_and...

   Given a description of the possible initial states of the world, a description of the desired goals, and a description of a set of possible actions, the planning problem is to synthesize a plan that is guaranteed (when applied to any of the initial states) to generate a state which contains the desired goals (such a state is called a goal state).

4. List of artificial intelligence projects - Wikipedia

   en.wikipedia.org/wiki/List_of_artificial...

   1 the Road, the first novel marketed by an AI. [75] AlphaFold is a deep learning based system developed by DeepMind for prediction of protein structure. [76] Otter.ai is a speech-to-text synthesis and summary platform, which allows users to record online meetings as text. It additionally creates live captions during meetings.

5. 10 AI Tools That Can Plan Your Next Vacation

   www.aol.com/lifestyle/10-ai-tools-plan-next...

   4. iPlan.ai. iPlan.ai creates detailed, customizable travel plans that adapt to user preferences for destinations, duration, and interests.It’s well-suited for users who enjoy crafting a ...

6. 10 AI Tools That Can Plan Your Next Road Trip

   www.aol.com/10-ai-tools-plan-next-145700892.html

   3. Analyze travel data. Analyzing travel data can make your trips more enjoyable and rewarding by discovering hidden insights and patterns. (And you can learn about other measures of success here

7. Graphplan - Wikipedia

   en.wikipedia.org/wiki/Graphplan

   The name graphplan is due to the use of a novel planning graph, to reduce the amount of search needed to find the solution from straightforward exploration of the state space graph. In the state space graph: the nodes are possible states, and the edges indicate reachability through a certain action. On the contrary, in Graphplan's planning graph: