I'm sorry the title might be misleading.
I'm currently working on a Q-Learning algorithm. I only can modify the Agent. And the runner doesn't implement episodes.
Is there any way to make the agent store its learned q-values each time in a separate file, in order to reuse them the next time it runs.
Related
Is there an easy way to set up a database that's accessible to several people that can do all the things a single user would do?
I'm studying Database 101 and I am currently doing a project with four other people and we're having trouble meeting up and doing it so it would be great if we could do it from wherever.
When I say "easy way" I mean without having the super-ultra-deluxe-enterprise-edition of software.
Can it be done with a "local" Dropbox folder?
What you can do at zero cost is to have one project master.
Distribute a copy to each member. Each will have to do completely separate tasks, like one for designing a form, one for adjusting a report, one for some code module, one for another code module.
When done, in the evening or what you agree upon, you collect the different versions with a list of what objects has been changed or added. Import these in your master, and then distribute this to the members as the current revised working copy.
It takes some discipline, but that's all. And all masters you save as a zip given a filename including the date and time. This way, nothing can get lost.
Using rails and postgresql.
I wrote my app without having in mind to use a master slave configuration.
Now, I've gotten master slave set up in the app and now I'm running into some technical debt. The same process in my app writes to the db and then immediately reads from the db. The read is not taking place on the read db but the data isn't there. Before, this wasn't efficient but it didn't cause any problems because both dbs were the same. Now, this is blowing up in my face.
The problem for me is that its difficult to find all the places in the code where this problem exists. Can someone can please suggest to me a technique to get my tests to run in such a way where the reads and the writes use different dbs that aren't updated so that I can figure out where my issues are?
Other solutions will also be welcomed!
I strongly recommend you rethink your master/slave configuration or whether master/slave is even right for your application.
It's not "tech debt" to build a system that assumes data written to persistent store can be read back immediately. It's normal and correct. While you might reasonably be able to avoid the pattern
write A, ..., look up A.key
with various simple cache schemes, trying to code around e.g.
write A, ..., complex query that *might* fetch A
requires you to retain a copy of A and determine whether it would satisfy the WHERE clause of the query in separate code, simply because you can't rely on the query results. Unless your system is very small and simple, trying to do this system-wide will produce a super-complex, fragile, expensive, and ugly code base. I strongly recommend you don't try it.
The usual purpose of a master/slave persistent store organization is to off-line read traffic that's not time-dependent on writes. For example, if your system mines data to produce summaries accessible to users, you'd offline the metric computation and have it mine the slave. This prevents mining queries from drawing resources away from user request handling. The small delay between write on master and copy to slave is no problem.
If your app is struggling because there's too much load on persistent store, you probably want partitioned data (sometimes called sharding), not master/slave. Partitioning can expose you to a different kind of problem: no cross-partition transactions. But this is usually easier to work through than what you're attempting.
After studying this area, I agree with Gene that master slave should only be used for reads that have been written a significant time before the read.
My ORIGINAL concept was that its better to utilize a functional programming style whereby the process retains all the information in the parameters and then doesn't make recourse to the database. The downside of this approach is that the human mind has a hard time with functional programming and in a massive computer program it makes sense to not insist on this added complication.
If you want to write a functional method or process then that is great and very efficient but there shouldn't be anything in the code that insists on this.
I'm writing a very long integration test for a wizard that has around 15 steps. Each of these steps has around 20 inputs/select boxes.
I started out using static data in my tests, but now I've begun to write stuff like selecting a random value from a select box, and clicking a random radio button for an option. This does seem like it's more capable of catching bugs, for example; one of the buttons on the page might not be rendered correctly and therefore the value never gets saved to the database - this would never have been found using static data that selects the same option every time. Alternatively, I could manually write out every possible option that could be chosen, but that'd take an eternity to do.
I hear that one of the main reasons not to use random data is that you can not explicitly see the data used in your tests and it can make failing tests hard to resolve.
Is this path that I'm going down one to be avoided? or is testing in this manner something that's generally done?
This is inherently a QA question rather than an automation one. You'll need to ask yourself and your team whether or not testing every single permutation is even worth the time and effort. Usually it is not. In my experience it's best to get information on the most common user journeys in your wizard and branch out from there. I would tackle those first from an automation standpoint and then move onto lower risk paths.
I like to use random data in certain low-risk areas that the devs confirm are relatively inconsequential (for example, a true/false radio box) and you can always make sure you are logging output properly to catch bugs.
I want to develop a app/software which understand text from various input and make Decision according to it. Further if any point the system got confused then user can manual supply the output for it and from next time onwards system must learn to give such output in these scenarios. Basically system must learn from its past experience. The job that i want handle with this system is mundane job of resolving customer technical problems.( Production L3 tickets). The input in this case would be customer problem like with the order( like the state in which order is stuck and the state in which he wants it to be pushed) and second input be the current state order( data retrieved for that order from multiple tables of db) . For these two inputs the output would be the desired action to be taken like to update certain columns and fire XML for that order. The tools which I think would required is a Natural Language processor( NLP) library for understanding text and machine learning so as learn from past confusing scenarios.
If you want to use Java libraries for your NLP Pipeline, have a look at Opennlp.
you've a lot of basic support here.
And then you've deeplearning4j where you've a lot of Neural Network implementations in java.
As you want a Dynamic model which can learn from past experiences rather than a static one, you've a number of neural netwrok implementations which you can play with in deeplearning4j.
Hope this helps!
I know there is a lot of talk about BPM these days and I am conscious that some may see it to be a craze rather than a fundamentally important piece of software.
As someone from what most would call 'The Business', I have been doing my best to learn about BPM to ensure we continue to make decisions that not only make sense to the business, but IT as well.
I have noticed while reading that mention is made to application workflow when sometimes discussing BPM. I hadn't given this much thought until recently.
Therefore, what is the difference? When would you use one and not the other?
BPM is about the process and improving it, which takes into account users and potentially more than one application,e.g. an ERP system may have more than one application to it, though there may be other uses of the term. Note that the process could be viewed without what applications or technologies are used.
Application workflow is how an application is used to go from a to b. Here it is a specific set of code that is used and what happens over the course of an application getting from a to b. In this case, the application is front and center rather than the process.
Does that provide an answer? Another way to think of it is that multiple application workflows can make up a system which is used in a process that can have BPM applied to it.
Late to the game, but workflow is to database as BPMS is to DBMS. (Convenient how the letters line up, huh?)
IOW, BPM(S) is traditionally meant to refer to a particular framework/application that allows you to manage business processes: defining them, storing them, versioning them, measuring them, etc. This is similar to how a DBMS manages databases.
Now, a workflow is a definition, much like a database is a definition. In the former case, it is a definition of operations/work (Fufill Order), steps thereof (Send Invoice) and rules/constraints on the work (If no stock, send notice). In the latter, similar case, it is a definition of data structure (CREATE TABLE) and constraints (InvoiceTotal must be > $0.00).
I think this is a potentially confusing subject, particular as some development environments use a type of process flow model to generate user facing applications (I'm thinking about Outsystems here, for example).
But, for me, the distinction is crystal clear. Application workflow, as people talk about it, refers to a user's path through an application, i.e. the pages they complete/visit, the data they enter, etc. on their way to completing a transaction of some sort. Application orkflow is a poor term for this though, I think application flow would be more meaningful.
BPM on other hand, is about modelling and executing a workflow process. By workflow, in this context, I mean a series of discrete steps (or tasks) that have to be completed (either programmatically or via human interaction) in a certain order to complete a process. These tasks can be implemented as individual application modules (each with their own "application workflow", see above). The job of the workflow engine is to make sure that these separate steps are assigned to the right people (of groups of people) in the right sequence, and that overall the process completes in an orderly way.
I don't think there's a clear answer to this at all. These are words, as opposed to theoretical concepts. If you add the word "checklist" into the mix - that just turns out to be a linear version of a process (but you can have conditionals in checklists - making them a workflow).
I am not sure how to help in reframing this question, but it's almost as if no answer can ever be possible. My own thoughts are at https://tallyfy.com/improving-efficiency-workflow-vs-business-process-management/