Author: Shlomi Fish

# Freecell Solver’s To-do list

Shlomi Fish
shlomif@cpan.org

## Pressing

## Non-pressing

- Investigate whether one can optimize `forking_range_solver.c` by making the requests and responses shorter.

  - Eliminate reporting the iterations.

- Find how well the solver performs with different permutations of the order of columns/freecells.

  - See if it’s possible to combine several scans on such different permutations.

- Write a "simulator" for new flare-based runs to see how they improve on the existing runs. It will process the scans' command line based on their end results and performance and will generate the new estimated performance.

- Write the split-dbm-solver which stores the results on the disk for every non-reversible-moves offset, and fully-connected-components.

- Refer to `expand-solitaire-multi-card-moves` from the fc-solve process.

- Create a displayer for fc-solve’s solutions which will allow seeing where a card was moved from (using a colored →) and where it was placed.

  - Create a GUI version.

- If `-opt` is specified for the flare, then make sure that if the flares loop tries to preempt it when it’s doing the optimization scan, then the optimization scan should proceed to run until it ends.

  - Not sure about it.

- Implement more of Kevin Atkinson’s Common Lisp solver’s atomic move types, and try to construct good heuristics out of them.

- Play with writing a memory-re-cycling Soft-DFS scan: if a sub-tree was marked as a dead-end, then its states might be able to be placed on a linked list of states that can be reused.

- PySolFC Deal No. 48007594292403677907 :

    shlomif:~$ make_pysol_freecell_board.py -t -F 48007594292403677907 | fc-solve -l cpb -sam | grep ^Move | wc -l
    106
    shlomif:~$ make_pysol_freecell_board.py -t -F 48007594292403677907 | fc-solve --method a-star -to 01234675 -asw 300,1500,0,2,50000 -sam | grep ^Move | wc -l
    105
    shlomif:~$ make_pysol_freecell_board.py -t -F 48007594292403677907 | fc-solve --method a-star -to 01234675 -asw 40,2,40,0,40 -sam | grep ^Move | wc -l
    121
    shlomif:~$ make_pysol_freecell_board.py -t -F 48007594292403677907 | fc-solve --method a-star -to 0123467589 -asw 300,1500,0,2,50000 -sam | grep ^Move | wc -l
    100
    shlomif:~$ make_pysol_freecell_board.py -t -F 48007594292403677907 | fc-solve --method a-star -to 0123467589 -asw 300,1500,0,2,40000 -sam | grep ^Move | wc -l
    106
    shlomif:~$ make_pysol_freecell_board.py -t -F 48007594292403677907 | fc-solve --method a-star -to 0123467589 -asw 300,1500,0,2,60000 -sam | grep ^Move | wc -l
    91

    shlomif:~$ make_pysol_freecell_board.py -F -t 91151234961275807905 | ~/apps/test/fcs/bin/fc-solve  -p -t -sam --method a-star -to 0123467589 -asw 300,1000,0,2,90000 | grep ^Move | wc -l
    84

However this scan generates takes too much time for most boards (over 100K iterations).

- PySolFC deal No. 03620802041832966472:

    shlomif[fcs]:$trunk/fc-solve/source$ make_pysol_freecell_board.py -t -F 03620802041832966472  | ./scripts/summarize-fc-solve -- --method a-star -to 0123467589 -asw 300,1500,99,2,65000
    Verdict: Solved ; Iters: 156 ; Length: 87

- I solved it at length 87.

  - PySolFC deal No. 54369539487824719321:

    shlomif[fcs]:$trunk/fc-solve/source$ make_pysol_freecell_board.py -F -t 54369539487824719321 | ./scripts/summarize-fc-solve --method a-star -to 0123456789 -asw 3000,100,60,0,500
    Verdict: Solved ; Iters: 1325 ; Length: 115

- Shlomi Fish solved it in under 110 moves.

  - PySolFC deal 96166640969002647853:

    shlomif[fcs]:$trunk/fc-solve/source$ make_pysol_freecell_board.py -F -t 96166640969002647853 | ./scripts/summarize-fc-solve --method a-star -to 0123467589 -asw 370,0,0,2,90000
    Verdict: Solved ; Iters: 615 ; Length: 77

- Shlomi Fish solved it in 77 moves.

  - PySolFC deal 26892246862786948900:

    shlomif[fcs]:$trunk/fc-solve/source$ make_pysol_freecell_board.py -F -t 26892246862786948900 | perl scripts/summarize-fc-solve -l qsi --flares-choice fc_solve
    Verdict: Solved ; Iters: 195331 ; Length: 98
    shlomif[fcs]:$trunk/fc-solve/source$ make_pysol_freecell_board.py -F -t 26892246862786948900 | perl scripts/summarize-fc-solve --method a-star -asw '1,0,4,0,4'   --flares-choice fc_solve
    Verdict: Solved ; Iters: 111 ; Length: 92

- Shlomi Fish solved it in 92 moves.

  - Add the new Freecell Solver-compatible game variants of PySolFC.

  - Convert magic rank constants such as 1 or 13 to FCS_MAX_RANK and FCS_RANK_ACE/etc.

  - Investigate:

    $ make_pysol_freecell_board.py -F -t 00682189035907813607 | perl ../scripts/summarize-fc-solve -l qsi
    Verdict: Solved ; Iters: 157905 ; Length: 109
    $ make_pysol_freecell_board.py -F -t 00682189035907813607 | perl ../scripts/summarize-fc-solve --method a-star -to '01234567' -asw 1 -opt
    Verdict: Solved ; Iters: 433 ; Length: 89

- Consider adding the `restrict` keyword:

  - http://stackoverflow.com/questions/776283/what-does-the-restrict-keyword-mean-in-c

  - https://duckduckgo.com/?q=restrict+keyword+c&ia=web

## Long-term

- Integrate the patsolve’s prioritization and mixed BFS/DFS scan.

- Update the architecture document.

- Make a super-strict parsable-output without all the quirks of -p -t (see Games-Solitaire-Verify for why).

  - Perhaps see: https://groups.yahoo.com/neo/groups/fc-solve-discuss/conversations/topics/1264 .

- Write a multi-threaded version.

- Add a switch to ask the user if he wants to continue and enter a bigger iterations limit.

- Check for unmalloced data and if so gracefully exit.

- Experiment with a delta-based state storage.

  - see delta_states_debondt.c - port it to the main libfreecell-solver.

  - see: http://fc-solve.shlomifish.org/to-do.html#orig_calc_states .

- Adapt the scans based on the parameters of the initial board.

  - Try to find a correlation between various parameters of the initial board (such as those calculated in the A* scan or the number of steps required to sort the cards in each column by rank), and the performance of various scans and then:

    1. Calculate the initial parameters on startup.

    2. See what would be a good meta-scan based on them.

    3. Use it.

- Unit-test `fc_solve_compare_lru_cache_keys` in `scans.c`.

- Interactive mode? Continue a scan that reached its limit.

- Adapt `-dto2` to other parameters aside from depth, such as total-number-of-cards-in-the-foundations or maximal foundation value.

- Set up a `-dto2` like scheme for `--method a-star` where we change the tests order based on the depth/etc.

## To be considered

- Make the code splint-clean.

- Write a multi-process client/server program.