Checkers Solution

[Allen Yerke]

Asolved game is a game whose outcome (win, lose or draw) can be correctly predicted from any position, assuming that both players play perfectly.This concept is usually applied to abstract strategy games, and especially to games with full information and no element of chance;solving such a game may use combinatorial game theory and/or computer assistance.

Despite their name, many game theorists believe that "ultra-weak" proofs are the deepest, most interesting and valuable. "Ultra-weak" proofs require a scholar to reason about the abstract properties of the game, and show how these properties lead to certain outcomes if perfect play is realized.[citation needed]

Given the rules of any two-person game with a finite number of positions, one can always trivially construct a minimax algorithm that would exhaustively traverse the game tree. However, since for many non-trivial games such an algorithm would require an infeasible amount of time to generate a move in a given position, a game is not considered to be solved weakly or strongly unless the algorithm can be run by existing hardware in a reasonable time. Many algorithms rely on a huge pre-generated database and are effectively nothing more.

As a simple example of a strong solution, the game of tic-tac-toe is easily solvable as a draw for both players with perfect play (a result manually determinable). Games like nim also admit a rigorous analysis using combinatorial game theory.

Whether a game is solved is not necessarily the same as whether it remains interesting for humans to play. Even a strongly solved game can still be interesting if its solution is too complex to be memorized; conversely, a weakly solved game may lose its attraction if the winning strategy is simple enough to remember (e.g., Maharajah and the Sepoys). An ultra-weak solution (e.g., Chomp or Hex on a sufficiently large board) generally does not affect playability.

In game theory, perfect play is the behavior or strategy of a player that leads to the best possible outcome for that player regardless of the response by the opponent. Perfect play for a game is known when the game is solved.[1] Based on the rules of a game, every possible final position can be evaluated (as a win, loss or draw). By backward reasoning, one can recursively evaluate a non-final position as identical to the position that is one move away and best valued for the player whose move it is. Thus a transition between positions can never result in a better evaluation for the moving player, and a perfect move in a position would be a transition between positions that are equally evaluated. As an example, a perfect player in a drawn position would always get a draw or win, never a loss. If there are multiple options with the same outcome, perfect play is sometimes considered the fastest method leading to a good result, or the slowest method leading to a bad result.

Perfect play can be generalized to non-perfect information games, as the strategy that would guarantee the highest minimal expected outcome regardless of the strategy of the opponent. As an example, the perfect strategy for rock paper scissors would be to randomly choose each of the options with equal (1/3) probability. The disadvantage in this example is that this strategy will never exploit non-optimal strategies of the opponent, so the expected outcome of this strategy versus any strategy will always be equal to the minimal expected outcome.

Although the optimal strategy of a game may not (yet) be known, a game-playing computer might still benefit from solutions of the game from certain endgame positions (in the form of endgame tablebases), which will allow it to play perfectly after some point in the game. Computer chess programs are well known for doing this.

To deliver on complex business requirements, makers often can end up with highly advanced solutions that customize and extend the Microsoft Dataverse platform. With advanced implementations come an increased risk where performance, stability, and reliability issues become introduced, which can negatively impact the user experience. Identifying and understanding how to resolve these issues can be complicated and time consuming. With the solution checker feature, you can perform a rich static analysis check on your solutions against a set of best practice rules and quickly identify these problematic patterns. After the check completes, you receive a detailed report that lists the issues identified, the components and code affected, and links to documentation that describes how to resolve each issue.

When you install the solution checker in your environment, the Solution check column becomes available in the Solutions list. This column displays the solution analysis states for a solution.

When a solution check is completed, you can view the analysis report in the portal, or you can download the report from your web browser. In the portal, you have options to sort results by Issue, Location or by Severity and view detailed information for issues detected in your solution.

The solution check results are also available for download. The solution checker zip file is downloaded to the folder specified by your web browser. The download report is in Excel format and contains several visualizations and columns that assist you in identifying the impact, type, and location of each issue detected in your solution. A link to detailed guidance about how to resolve the issue is also provided.

You can run solution checker rules in your development environment to detect issues much sooner as you create your solution resources. This is currently supported for web resources (JavaScript and TypeScript). For more details, go to the NPM package @microsoft/eslint-plugin-power-apps.

The following table lists the component type, rule description, severity, and category. Critical violations are blocked or warned when configured for solution checker enforcement with managed environments. More information: Use solution checker in Managed Environments

1) If you enter wrong coordinates into the solution checker...a message shows " Those coordinates are not correct. You have 9 tries left." So now I 'm just curious to what happens when someone enters too many wrong attempts. Are you timed out? For how long?

Airsoft...thanks for this. I tried this code on our cache and it seems to work well in the app for what I want it to do. If you click on the link in the app, it takes you to the geocaching.com cache page then forwards the page straight to the in-house solution checker. I think I'll give this a try, see if cachers end up using it or not. Of course I like the idea of using GeoCheck for the stats purposes but I like the idea of trying the "in-house" products too. You can see the code put to use in our cache GC5Q2A0. Thanks again.

Honestly, in SOME scenarios the solution checker on the cache page is useful because you can see the options in front of you and if you miss one number you can try again. Typically other coord checkers give you at least 10 tries per day so the solution checker gives 10 tries in a certain period of time. In other scenerios where you have a puzzle that may include a keyword, you probably would use certitude for that. Or a puzzle involving multiple steps again another checker would do. I've noticed on a few newer puzzle caches in my area the solution checker is used for non-cipher puzzles and it is more convenient since once you get it right it will automatically insert the corrected coords for you.

I believe the solution checker is mostly compatible for caches where you are given variables such as "final is at N 43 00.xyz W 077 45.910" because you can look up and down on the screen to check (like you would when entering coords in a GPS) instead of going from one page to another. I still would use other checkers for caches that use ciphers and note that the solution checker doesn't offer the keyword ability so you still would have to use another checker if the solution were a keyword, and/or if it included multiple steps.

I can't think of a third-party checker that only allows 10 attempts per day. The three most popular third-party checkers all have the same limit of 10 attempts per 10 minute period as the new solution checker.

Not everyone considers this to be convenient. In fact, some of us find it downright inconvenient and would like an option to disable this portion of the feature altogether. Having the corrected coordinates on the cache listing interferes with my typical workflow using GSAK. If I need to use a built-in solution checker and get a success, the first thing I do is scroll up to the top and restore the posted coordinates.

Certitude allows 10 attempts in a 10 minute period is correct, I didn't know that the solution checker was the same. Also, I'm curious as to why you would want to restore the posted coordinates if you had the corrected coordinates. That way you wouldn't have to solve it again as long as the coordinates remained the same.

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