lunarlander | Pygame based lunar Lander

 by   pyrex8 Python Version: Current License: MIT

kandi X-RAY | lunarlander Summary

kandi X-RAY | lunarlander Summary

lunarlander is a Python library. lunarlander has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However lunarlander build file is not available. You can download it from GitHub.

Pygame based lunar Lander. This project is inspired by the NOMAM Basic Ten-Liners competition, JS1K, and similar contest to squeeze a game into some ridiculously small amount of code. Use the left and right arrows and space bar for controls. r to reset and esc to exit.
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              lunarlander has a low active ecosystem.
              It has 6 star(s) with 9 fork(s). There are 1 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              lunarlander has no issues reported. There are 2 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of lunarlander is current.

            kandi-Quality Quality

              lunarlander has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              lunarlander 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

              lunarlander releases are not available. You will need to build from source code and install.
              lunarlander has no build file. You will be need to create the build yourself to build the component from source.

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            lunarlander Key Features

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            lunarlander Examples and Code Snippets

            No Code Snippets are available at this moment for lunarlander.

            Community Discussions

            QUESTION

            gym package not identifying ten-armed-bandits-v0 env
            Asked 2022-Feb-08 at 08:01

            Environment:

            • Python: 3.9
            • OS: Windows 10

            When I try to create the ten armed bandits environment using the following code the error is thrown not sure of the reason.

            ...

            ANSWER

            Answered 2022-Feb-08 at 08:01

            It could be a problem with your Python version: k-armed-bandits library was made 4 years ago, when Python 3.9 didn't exist. Besides this, the configuration files in the repo indicates that the Python version is 2.7 (not 3.9).

            If you create an environment with Python 2.7 and follow the setup instructions it works correctly on Windows:

            Source https://stackoverflow.com/questions/70858340

            QUESTION

            Is it possible to resolve TypeError: argument 'input' (position 1) must be Tensor error without retraining the model?
            Asked 2021-Apr-30 at 09:02

            I have made a model in PyTorch for use in an openAI Gym environment. I have made it in the following way:

            ...

            ANSWER

            Answered 2021-Apr-30 at 09:02

            This error is not related to your model. forward function only returns the probability distribution but what you need is the action and corresponded probability (output of Policy.act).

            Change your code from

            Source https://stackoverflow.com/questions/67316491

            QUESTION

            Keras fit takes so much time
            Asked 2020-Dec-19 at 19:16

            I'm recently learning deep reinforcement learning and I wanted to apply what I learned to a problem from gym using Keras.

            During training I realized that it is too slow, after checking the reason I saw that "fit" function takes so much time.

            Running each episode takes 3-4 minutes.

            Is there something wrong at what I'm doing? Or can you suggest an improvement?

            ...

            ANSWER

            Answered 2020-Dec-19 at 19:16

            Your problem is not in the fit call, but in the loop that you have in the replay() method. Try always substituting loops by numpy operations in these cases, that make the operations much more agile.

            Replace your replay method by the following one and let me know if it works faster for you

            Source https://stackoverflow.com/questions/65359792

            QUESTION

            How to configure Dueling Double DQN input_shape for samples with a shape of (169, 3) each?
            Asked 2020-Dec-10 at 17:09

            TLDR

            The input shape of each sample for my DoubleDuelingDQN is (169, 3). The output of that DDDQN shall be of shape (3) for 3 corresponding actions. Currently, when I call

            ...

            ANSWER

            Answered 2020-Dec-10 at 17:09

            You can't use Dense layers on 2D inputs (i.e. inputs that are 3D, with the batch dimension). It will only take the last dimension as its input. Dense layers work with 1D input tensors, provided as a 2D batch.

            Either add a Flatten(shape=-1) layer to flatten your input (e.g. to a (batch_size, 169*3) tensor), or use a convolutional network.

            Also your self.A layer appears to provide the q-value for each action, given a state. The advantage would be the action values - the value estimate. I think that's what you're calculating in call()

            If the flatten doesn't fix your output shape, I'd double check the shapes of the arguments for Q, and the shape of the returned Q. print(Q.shape) will be your friend for debugging!

            Source https://stackoverflow.com/questions/65237345

            QUESTION

            Require subclass to implement a static method
            Asked 2020-Jul-30 at 19:17

            Coming from Python and Objective-C land, I may not fully understand what static methods are in Java, I think of them as "methods that operate on all members of the class" or "class-specific methods that are available when you don't have an instance of that class."

            But is there a syntax for saying: "This abstract superclass requires each concrete subclass to implement this static method"? I know that static abstract isn't permitted, but it would conceptually be something like this:

            ...

            ANSWER

            Answered 2020-Jul-29 at 20:19

            I tried your code(and other things surrounding this), and I'd like to tell you there's a way but I don't think there is.

            I would instead recommend using a utility class that supports this static functionality you're looking for.For example, a LanderUtility class that has static methods in it might solve this in a reasonable way.

            Mostly though, I don't think of using static methods in that way in Java. The real power in what is going on with this abstract class is that you can count on(somewhat) a certain type of behavior from a child. Notably, for this to matter, the child needs to be instantiated in the first place and you can use a normal, non-static method and have the child implement that instead.

            Source https://stackoverflow.com/questions/63161290

            QUESTION

            Does boolean variable need synchronization while checking in the given example?
            Asked 2020-Jun-13 at 13:59

            I'm exploring an example of a simple android game and I have a question about its synchronization logic.

            Given two fields:

            ...

            ANSWER

            Answered 2020-Jun-13 at 12:10

            You need to keep the 'synchronized' statements. If you don't (though note that android, which isn't really java, may not be adhering to the same memory model as actual java), then any thread is free to make a temporary clone for any field of any instance it wants, and synchronize any writes to the clone at some undefined later point in time with any other thread's clone.

            To avoid the issues with these 'clones'*, you need to establish CBCA relationships ("comes before/comes after") - if the thread model ensures that line X in thread A definitely ran after line Y in thread B, then any field writes done by line Y will guaranteed be visible in line X.

            In other words, with the synchronized statements, if the mRunLock lock in your run() method has to 'wait' for the setRunning method to finish running, you just established a CBCA relationship between the two, and it's crucial because that means the mRun write done by setRunning is now visible. If you didn't, it may be visible, it may not be, it depends on the chip in your phone and the phase of the moon.

            Note that boolean writes are otherwise atomic. So it's not so much about any issues that would occur if you read whilst the field is being written (that is not a problem in itself if the field's type is decreed as being atomic, which all primitives other than double and long are), it's ensuring visibility of any changes.

            In plain jane java you'd probably use an AtomicBoolean for this and avoid using any synchronized anything. Note also that nesting synchronized() on different locks (you lock on mSurfaceHolder, and then lock on mRunLock) can lead to deadlocks if any code does it 'in reverse' (locks on mRunLock first, then locks on mSurfaceHolder).

            Are you running into any problems with this code, or just wondering 'is it correct'? If the latter: Yes, it is correct.

            *) Whilst this clone thing sounds tedious and errorprone, the only alternative is that any field write by any thread is immediately visible by any other thread. That would slow everything waaaaay down; the VM has no idea which writes have the potential to be read soon by another thread, and if you know anything about modern CPU architecture, each core has its own cache that is orders of magnitude (100 to 1000 times!) faster than system memory. This alternative of 'all writes must always be visible everywhere' would pretty much mean that fields can never be in any caches ever. That'd be disastrous for performance. This memory model is therefore basically a necessary evil. There are languages that don't have it; they tend to be orders of magnitude slower than java.

            Source https://stackoverflow.com/questions/62359342

            QUESTION

            Custom loss function : NotImplementedError: Cannot convert a symbolic Tensor (truediv_2:0) to a numpy array
            Asked 2020-Mar-22 at 21:09

            I am trying to write a custom loss function with an extra paremeter inside to implement an actor critic algorithm:

            ...

            ANSWER

            Answered 2020-Mar-21 at 13:12
            delta = Input(shape=(1), name='delta')
            

            Source https://stackoverflow.com/questions/60780509

            QUESTION

            Simulation of suicide burn in openai-gym's LunarLander
            Asked 2020-Jan-14 at 08:08

            I want to simulate suicide burn to learn and understand rocket landing. OpenAI gym already has an LunarLander enviroment which is used for training reinforcement learning agents. I am using this enviroment to simulate suicide burn in python. I have extracted the coordinates (x,y) from the first two values of state vector of this enviroment. From these values, considering y coordinates as the altitude; I have calculated velocity and accelartion of the falling lander using these equations

            ...

            ANSWER

            Answered 2020-Jan-14 at 08:08

            There are two issues with your code:

            1. delta_t should be 1.0/50.0 according to the lunar_lander source

            Source https://stackoverflow.com/questions/59589776

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

            Vulnerabilities

            No vulnerabilities reported

            Install lunarlander

            You can download it from GitHub.
            You can use lunarlander like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

            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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            https://github.com/pyrex8/lunarlander.git

          • CLI

            gh repo clone pyrex8/lunarlander

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            git@github.com:pyrex8/lunarlander.git

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