lcrl | Logically-Constrained Reinforcement Learning | Reinforcement Learning library

 by   grockious Python Version: 0.0.8 License: MIT

kandi X-RAY | lcrl Summary

kandi X-RAY | lcrl Summary

lcrl is a Python library typically used in Artificial Intelligence, Reinforcement Learning applications. lcrl has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install lcrl' or download it from GitHub, PyPI.

Logically-Constrained Reinforcement Learning (LCRL) is a model-free reinforcement learning framework to synthesise policies for unknown, continuous-state-action Markov Decision Processes (MDPs) under a given Linear Temporal Logic (LTL) property. LCRL automatically shapes a synchronous reward function on-the-fly. This enables any off-the-shelf RL algorithm to synthesise policies that yield traces which probabilistically satisfy the LTL property. LCRL produces policies that are certified to satisfy the given LTL property with maximum probability.
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            kandi-support Support

              lcrl has a low active ecosystem.
              It has 10 star(s) with 3 fork(s). There are 3 watchers for this library.
              There were 1 major release(s) in the last 6 months.
              There are 0 open issues and 1 have been closed. On average issues are closed in 30 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of lcrl is 0.0.8

            kandi-Quality Quality

              lcrl has 0 bugs and 0 code smells.

            kandi-Security Security

              lcrl has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              lcrl code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              lcrl is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              lcrl releases are not available. You will need to build from source code and install.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.
              It has 1878 lines of code, 64 functions and 56 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed lcrl and discovered the below as its top functions. This is intended to give you an instant insight into lcrl implemented functionality, and help decide if they suit your requirements.
            • Train a neural network
            • Train the DMPG model
            • Train a nfq module
            • Train the model
            • Generate a gif for a given policy
            • Compute the acceptance function
            • Returns the augmented action space
            • Reward the reward
            • Process layout
            • Perform a step
            • Find the shortest path between start and end
            • Reset the agent state
            • Convert from state to cell
            • Convert cell number to location coordinates
            • Step through the agent
            • Return the label for a given state
            Get all kandi verified functions for this library.

            lcrl Key Features

            No Key Features are available at this moment for lcrl.

            lcrl Examples and Code Snippets

            No Code Snippets are available at this moment for lcrl.

            Community Discussions

            QUESTION

            kableExtra inserts unwanted extra line into some cells, depending on cell value
            Asked 2021-Mar-17 at 17:34

            I am using kableExtra to generate an Rmarkdown table (in Rstudio 1.2.1335, Windows 10). One of the cells ends up with it's value pushed to another line which messes up the line spacing (see image below). The odd part is that if I manually replace that cell value in the matrix with another value, it sometimes fixes it, depending on the replacement value. My code is below (I have tried and failed to make a reproducible example - the problem only seems to crop up with my actual data).

            ...

            ANSWER

            Answered 2021-Mar-17 at 17:34

            I have identified the issue (thanks to the issues posted here, here, and here). The problem is that when two rows in the table are identical, a \vphantom{1} is inserted into the LaTex code for the first identical row, to differentiate the two identical rows. I noticed this when I examined the Latex file - the first row of the table was

            Source https://stackoverflow.com/questions/66645590

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install lcrl

            You can install LCRL using.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            Install
          • PyPI

            pip install lcrl

          • CLONE
          • HTTPS

            https://github.com/grockious/lcrl.git

          • CLI

            gh repo clone grockious/lcrl

          • sshUrl

            git@github.com:grockious/lcrl.git

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