Monthly Archives: March 2021

A chess engine usually analyzes thousands of outcomes before making an efficient move. Since the hardware and programming techniques are getting better year by year, chess engines are becoming more intelligent. Modern engines are more selective and have a better positional understanding.

If you construct a complete tree of all possible moves in a chessboard, you will get a total of 10120 moves. Thats an extremely large number.

To put this into perspective, there have been only 1026nanosecondssince the Big Bang and estimated1075atoms in the entire universe. These numbers are dwarfed by the number of possible moves in chess, making it one of the most complex board games.

There are literally hundreds of rating lists that measure the relative strength of chess engines, based on how many moves they make per minute. In addition to ranking chess engines from best to worst, these lists also provide margins of errors on the given ratings.

Among these rating lists, the most famous are CCRL (Computer Chess Rating Lists) and CEGT (Chess Engines Grand Tournament). Keeping both these ratings in mind, we are presenting the most advanced Chess Engines that demonstrate the machines domination over humanity.

CCRL Rating: 3229CEGT Rating: 3094

Hannibal is a Universal Chess Interface (UCI) engine that incorporates ideas from earlier engines, Twisted Logic, and LearningLemming. It uses the alpha-beta technique with many other chess specific heuristics and relies on a selective search method.

Besides incredible endgame knowledge, the engine has a good understanding of material imbalances.It also understands the fortresses and trapped pieces and can sacrifice material for the initiative on king attacks.

Furthermore, Hannibals time management is tuned for the Fischer time controls.

CCRL Rating: 3232CEGT Rating: 3098

Critter is the UCI chess engine available for Windows, Mac, Android, and Linux. You can use it for private purposes only. It was initially written in Delphi but later converted to C++ using Bitboard technology. This was done to enhance its performance on 64-bit processors.

This chess engine features null move pruning, forward pruning, principal variation search, parallel search with up to 8 threads, and blockage detection in the endgames.

CCRL Rating: 3533

SugaR engine is derived from Stockfish and supports up to 128 cores. Like other popular engines such as Stockfish, SugaR is not a complete chess program. It requires compatible GUI, such as XBoard with Arena, PolyGlot, Shredder, Sigma Chess, and Chess Partner.

Since the engine is distributed under the General Public License, you are allowed to modify and sell it.

CCRL Rating:3506

asmFish is a Stockfish engine port written in x86 assembly language. It usesBMI2 and AVX2 instructions optionally. It is assembled with FASM for Linux and Windows platforms.

asmFish is built with some structural optimization techniques, such as the elimination of piece lists. Critical functions dont conform to the x86 ABI, concerning the usage of register and calling convention. However, less time-critical functions were ported through GCC assembly output.

Nevertheless, the engine is NUMA (non-uniform memory access) aware and supports parallel search and large pages.

CCRL Rating: 3241CEGT Rating: 3123

Chiron is the commercial chess engine that supports both Universal Chess Interface and Chess Engine Communication Protocol, as well as several endgame tablebase and bitbase formats.

It applies a parallel search on multiprocessor architectures and implements pawn blockage detection that not only detects blockages in pawn endgame but also identifies other pieces on the board.

The latest version has been tuned deeply, especially in the context of passing pawns and mobility. Several advanced search enhancements have also been introduced, such asLazy symmetric multiprocessing, forward pruning, and NUMA awareness

CCRL Rating: 3253CEGT Rating: 3122

Equinox is a symmetric multiprocessing chess engine primarily developed by Giancarlo Delli Colli. It is inspired by popular open-source engines like Stockfish, Crafty, and Ippolit.

Equinox is active in several private engine tournaments, including Italian Open Chess Software Cups and Thoresen Chess Engine Competition.

CCRL Rating: 3261CEGT Rating: 3183

GullChess is an open-source chess engine that applies magic bitboards to determine sliding piece attacks. It is mostly written in the C++ programming language and contains only one source file.

Gull Engine features generic function templates in recursive search routines, as well as several other functions for move generation (excluding hash move and side to move).

CCRL Rating: 3284

Schooner uses alpha-beta search, late move reductions (LMR), principle search window (PVS), and single hash entry. It supports a subset of Universal Chess Interface to automatically play games without hogging a lot of resources.

Its performance has been improved significantly in recent years: a simpler evaluation inspired by Xiphos, staged move generation, and tons of testing and tuning are responsible for those improvements.

CCRL Rating: 3324CEGT Rating:3193

Xiphos is an open-source chess engine written in C and distributed under GNU General Public License. Its a UCI compliant engine that utilizes bitboards withERLEFmapping.

Xiphos uses sliding piece attacks, which are evaluated by either PEXT bitboards (for BMI2) or magic bitboards. If you want to try, you can run this engine on Windows, macOS, and Linux.

CCRL Rating: 3324CEGT Rating: 3153

Shredder is a commercial chess engine developed in 1993. It has won more than 20 titles, including World Microcomputer Chess Championship (1996, 2000), World Computer Chess Championship (1999, 2003), World Chess Software Championship (2010), and World Computer Speed Chess Championship (5 times).

Deep Shredder is the multiprocessor version of Shredder. It comes with a graphical user interface, developed by Millennium Chess System, which supports Universal Chess Interface and is compatible with other UCI engines available for Mac OS, Windows, and Linux.

WCCC 2011,Boootvs.Alex Morozov

CCRL Rating: 3326CEGT Rating: 3234

Booot is an open-source chess engine written in Delphi 6. It determines sliding piece attacks with rotated bitboards. It is packed with lazy SMP and a fully redesigned evaluation function.

The engine applies PVS with all basic search enhancements like late move reductions, null move pruning, and internal iterative deepening. The latest version supports multiprocessor architecture and has several assembly variants for 32 and 64 bits.

CCRL Rating: 3337CEGT Rating: 3209

First published in 2014,Andscacssoon evolved into one of the worlds best chess engines. It uses magicbitboardto speed up the attack calculations. It applies a principal variation searchwith a transposition tableinside an iterative framework.

Andscacs features static exchange evaluation and threaded parallel search. And it tries a hash move in quiescence search.

In order to make the engine more powerful and efficient (or minimize the standard deviation of static evaluation), researchers optimized 200 evaluation features with 750,000 positions.

Read: Googles AlphaZero AI Masters Chess and Go Within 24 Hours

CCRL Rating: 3347CEGT Rating:3211

Fizbois a Chess Engine Communication Protocol, first released in 2014. It is based onbitboardand uses population count instruction. For now, the engine is compatible with Windows and requires CPU withpop-countinstruction.

Besides iterative deepening, Fizbo performs parallel searches based on an enhanced PV splitting algorithm. Furthermore, the transposition table with 8-byte entries is used in the quiescence search.

CCRL Rating: 3386CEGT Rating: 3290

Ethereal is an open-source engine developed by Andrew Grant. Its a UCI-compliant chess engine first released in 2016 under the GNU GPL license.

Ethereal is greatly influenced by Stockfish, MadChess, and Crafty. In addition to the conventional alpha-beta framework, it uses various improvements, ranging from reduction and pruning to extension.

CCRL Rating: 3430CEGT Rating: 3319

Fireis a free chess engine that was used to be open source but later became a closedWindows executable, available for new Intel processors. It was initially known as Firebird and later renamed to Fire due to the trademarknamingconflict.

The Fire engine features magicbitboards, Syzygytablebases, configurable hash, andmultiPV. You can configure it with over 70 Universal Chess Interface options, and applySMP parallel search.

CCRL Rating: 3508CEGT Rating:3424

Komodo was derived from an older search engine, Doch, as a major rewrite and a port of Komodo to C++11. Since it relies on evaluation (instead of depth), it has a quite different positional style.

The engine supports up to 64 cores, Syzygy endgame tablebase, and Fischer random chess. Kodomo lets you save the engines analysis of a position so you can check it later and resume analysis. You can also control how the engine makes long-term sacrifices of pawn structure for dynamic play.

Komodo has won three-times Top Chess Engine Championship.

CCRL Rating: 3529CEGT Rating:3444

Houdini is known for its engines positional style, ability to defend strongly, tenacity in hard positions, and escape with a draw.

So far, it has won 3 seasons of Top Chess Engine Championship.

The new version of Houdini comes in 2 variations Standard and Pro. While the previous version supported up to 8 processor cores only, the Pro version supports up to 128 cores and 128 GB of RAM. It is NUMA aware and can utilizeNailmov endgame table bases.

Read: 15 Advanced Artificial Intelligence Projects

CCRL Rating: 3463CEGT Rating: 3467

Inspired by Deepminds research about AlphaZero and AlphaGo Zero, Leela Chess Zero relies on a self-taught neural network to make smart moves. The network learns through deep learning techniques by playing against itself millions of times.

Instead of using conventional AlphaBeta search with handcrafted evaluation function, it utilizes a type of Monte Carlo Tree Search (MCTS) known as puct. To achieve its full potential, you need to run the chess engine on CUDA-supported GPU.

CCRL Rating: 3564CEGT Rating: 3512

Stockfish is an open-source UCI engine available for various desktop and mobile platforms. It is based on another open-source chess engine namedGlaurung.

Read: 8 Best Artificial Intelligence Programming Languages

Written in C++, the engine can utilize up to 512 CPU cores. The maximum size of its transposition table is 1 Terabyte. Beside implementing an alpha-beta search, the engine features aggressive pruning and late move reductions.

Note: Since CCRL and CEGT rating lists change continuously, the ranking can differ from time to time.

See the rest here:

18 Best Chess Engines of 2021 | Based On Their Ratings ...

INTRODUCTION

Throughout history, chess was revolutionized several times.

In the late 19th century, the first World Champion Wilhelm Steinitz provoked his opponents to attack him vigorously and laid the foundations of positional chess.

In the middle of the 20th century, the sixth World Champion Mikhail Botvinnik started devoting an enormous amount of time to physical and chess preparation before the tournaments and matches, announcing the era of strict chess professionalism.

In the 1970s, largely under the influence of eleventh World Champion Robert James Fischer, the opening theory went through massive changes. New opening systems such as the Hedgehog were introduced and new ideas were discovered in ancient opening systems, demonstrating the inexhaustible nature of chess.

Nothing else, however, has revolutionized chess so much as the appearance of computer chess engines. Nowadays, even the biggest beginners are familiar with the terms Stockfish and Rybka (especially when they are shouting their names in online chats while kibitzing the games of top chess players). Even a chess computer on your mobile phone is stronger than a grandmaster nowadays. It is not surprising players have started using them as a tool and learning from them.

Even though we all embrace computer chess engines as something normal and use them on a daily basis, most of us arent familiar with the challenges and problems previous generations had to face in order to create one. Who devised the first computer chess engine? How long did it take for computers to become stronger than humans? What is the difference between classical computer chess engines and Googles Alpha Zero?

In this article, we will answer these questions and take a closer look at the history of computer chess engines.

In 1769, French illusionist Francois Pelletier was performing an act in front of Maria Theresa of Austria, at the Schnbrunn Palace in Vienna. Among the onlookers was Hungarian inventor and author Wolfgang von Kempelen. Inspired by Pelletiers performance, Kempelen immediately started building the invention which would later become one of the most notorious hoaxes in the entire history.

Next year, in 1770, at the exact same place, Kempelen exhibited the Turk the first chess-playing automaton in history. Its complicated construction consisted of several compartments with various operational mechanisms. It incorporated a life-sized model of a human, dressed in traditional oriental clothes (hence its name).

Turk was capable of playing chess on its own and beating human opponents. It was even able to recognize illegal moves and force its opponents to take them back. In one exhibition, it even solved the difficult knight-tour-around-the-board puzzle.

There was just one problem. It was all fake. The Turk was not the one making all the moves. A human hidden inside it was.

You see, during the construction, Kempelen envisioned several hidden compartments, big enough to fit an adult. He even made sliding hallways, through which a person was able to move from one compartment to another. It was important to preserve the illusion before each exhibition, Kempelen would invite the audience to examine the automaton, during which the operator of the machine would remain hidden.

And it worked? Kempelen toured Europe exhibiting his invention until his 1804. After his death, the machine changed several owners and continued playing chess until 1854, when a fire in Philadelphia sealed its fate. It is amazing no one realized the fraud during the Turks lifetime.

Thus, the first computer chess engine was a major commercial success.

However, if we disregard several similar automatons, the development of chess engines was stalled during the next 100 years. The real breakthrough happened only in the late 1940s and early 1950s. And just like with many other technological advances, a major historical event fulfilled the role of the catalyst.

During World War II, Axis and Allies leadership spent a lot of time hiring top scientists and gathering them into teams. The purpose was clear winning the war. Greatest minds of the 20th century devoted their wartime years to developing technology and weapons that will help overpower the enemy. The science was in service of the war industry.

In spite of that, the war led to a startling amount of breakthroughs. Scientists laid a foundation for a number of new fields. In the context of this article, computer science is of particular interest. Two famous names played the crucial role in its development Claude Shannon and Alan Turing.

Shannon is widely recognized as the father of the modern information theory, while Turing is the father of the modern computer (Turings machine!). Their contributions to the field of computer science are well known. What is perhaps lesser known, is that Shannon and Turing are also fathers of chess computer engines.

After finishing their PhDs on the eve of the war, Shannon and Turing both started working on cryptanalysis, in USA and UK, respectively. They closely followed each others work and even met in person back in 1943, during Turings two-month stay at Bells Lab in New York, where Shannon was working. After the war ended, they both took an increased interest in programming a chess computer.

(Main source describing the relationship between Shannon and Turing: Life In Code And Digits When Shannon Met Turing)

In 1949, Shannon published an iconic paper titled Programming a Computer For Playing Chess, in which he described an algorithm for the chess-playing machine. Simultaneously, Turing was developing his own chess playing program. His work on Turbochamp started back in 1948 and finished in 1950.

(Link to Shannons article)

It is noteworthy to mention Turing programmed Turbochamp on paper, without access to an actual computer. He tried testing it on Ferranti Mark I the first commercially available computer and failed. In the end, he tested it manually (!) in a friendly chess game in 1951.

(51 years later, none other than Garry Kasparov tested Turbochamp. The program didnt stand a chance, but the greatest players of all times recognized how tremendous Turings achievement was source: Alan Turing Created A Chess Computer).

It is not yet certain whether Shannon and Turing worked independently or were inspired by each other the content of their conversations in 1943 is not known. However, even if they didnt collaborate, their contributions were immense. Subsequent generations of computer chess developers all stood on the shoulders of these two giants.

In 1951, Turings colleague Dietrich Prinz managed to implement the algorithm on Ferranti Mark I and created a program capable of solving mate in two. In 1956, a team of scientists led by Stan Ulam (one of the inventors of the h-bomb)created a program capable of playing chess on a 66 board. And finally, in 1957, IBM engineer Alex Bernstein created the first automated program fully capable of playing a complete game of chess.

The era of computer chess has officially begun.

The first computer chess engines were rather weak and primitive. During the 1960s and the 1970s, however, their strength increased rapidly. Two major factors contributed to this qualitative leap:

In the 1960s and 1970s, algorithms for the computer chess engines were significantly improved. The foundation was set by the genius of John Von Neumann, who developed the MiniMax algorithm, perfectly suited for the game of chess (it minimizes the score of one player while maximizing the score of another). In the decades that followed, MiniMax search was improved with advanced heuristic techniques and iterative deepening, which gradually increased the depth of the search by MiniMax.

The greatest restriction for Turing and other pioneers was computing power. In the 1960s and 1970s, however, hardware speed increased exponentially according to Moores law, the computing power doubled every two years. It allowed the implementation of advanced algorithms the search time for MiniMax was significantly decreased.

It was not only the matter of raw computing power, though. In the 1960s and 1970s, computer chess gained prominence. The first all-computer chess championship was staged in 1970 in New York. Shortly afterward, in 1974, first World Chess Computer Chess Championship was staged in Stockholm. The appearance of the scene inevitably led to the foundation of specialized companies which started developing customized chess playing software and hardware. Which allowed computer chess engines to get even better.

How good get better was? How good were computer chess engines compared to humans at a time? Experience showed good enough to beat an amateur, not good enough to compete with a master.

For instance, in 1967, MacHack VI became the first computer chess engine to beat a human opponent. Its playing strength revolved around 1300 USCF rating. But already in 1976, a significant leap happened chess computer engine Chess 4.5 won the Class B Section of the Paul Mason tournament in Northern California. In 1977 it also won Minnesota Open with the performance rating of 2271 and beat a Class A player Stenberg rated 1969.

However, the computers werent on equal terms with stronger humans. In 1968, International Master David Levy bet 3000$ he would be able to beat any chess computer engine in the next 10 years. In 1977, he won his bet in a match against chess computer engine KAISSA. He also beat the newer version of MacHack in 1978.

Therefore, at the end of the 1970s, could compete against humans, but couldnt play on a master level.

But then the 1980s arrived.

By the start of the 1980s, computer chess engine programming has become a lucrative business. Personal computers have become widespread in households. The interest in customized and specialized software including computer chess engines exploded. In 1982 alone, computer chess companies topped 100 million in sales.

It is not surprising, thus, that computer chess engines continued improving. In 1980, their programming became a serious competition. Edward Fredkin, professor of computer science at Carnegie Mellon University, introduced the Fredkin Prize. He offered monetary prizes for various achievements in the world of computer chess programming (5000$ for the first engine to reach Master level, 10000$ for the first engine to reach Grandmaster level, 100000$ for the first engine to beat the World Champion).

The race was on. The number and strength of computer chess engines continued increasing.

Fredkins colleague from Carnegie Mellon University led the way. The most notable project and the spearhead of an entire generation is Deep Thought the first chess computer engine which reached Grandmaster Level. In 1988, it shared the first place with Grandmaster Tony Miles in US Open Championship. In 1989, it easily beat International Master David Levy four games to zero.

The downfall of humanity seemed inevitable. In the search for its Champion, it turned to the reigning World Champion and arguably the greatest player of all times Garry Kasparov. First, in an iconic simultaneous exhibition in Hamburg in 1985, he played against 32 (!) strongest chess engines and beat all of them (!!). Then, in 1989, he faced Deep Thought in a two-game match, which he also won.

(Source: Kasparov And Thirty Years Of Computer Chess)

Therefore, in his encounters with engines in the 1980s, Garry became the chosen one.

Alas, in the 1990s, he too would fall.

Thus, in 1989, humanity won the battle, but not yet the war. In the 1990s, many more clashes between humans and computer chess engines were held. Top chess engines even competed in elite chess tournaments with mixed success. Several human vs machine matches were organized, but none of them became famous as the match in which the engine defeated the World Champion in 1997.

In 1989, researchers involved in the Deep Thought project were hired by IBM. They started developing a more powerful version of the engine.

The name of the project was Deep Blue. In 1996, only 7 years after the Kasparov Deep Thought match, round two of man vs. machine was held: the first Kasparov Deep Blue match. In the very first game, Deep Blue shocked Kasparov and became the first chess computer engine to beat a World Champion in a classical game. However, Garry composed himself and won the match with the result 4-2, prolonging the inevitable once again.

The failure didnt disheartenDeep Blue programmers. During the next year, they continued to improve the engines strength. They even hired Grandmaster Joel Benjamin as a consultant to help them build the opening book. After thorough preparation, they challenged Kasparov to a rematch again and as they say the rest is history.

In the celebrated match, Kasparov won the first game. But the engines counterintuitive 44th move confused him. It shook his confidence and he missed serious drawing chances in the 2nd game. Then Deep Blue crushed him in 6th game with a knight sacrifice early in the opening. This sealed Kasparovs fate and earned Deep Blue team the Fredkin Prize.

(Source: Deep Blue Inventors Win Fredkin Prize)

After the match, he claimed IBM cheated and that a human was actually making the moves (Joel Benjamin). Other sources speculated a bug in Deep Blues code brought him victory.

(Source: Did Deep Blue Beat Kasparov Because Of A Glitch?)

In any case, 1997 symbolically marked the end of human domination over the chess computer engines.

However, humans didnt yet resign.

After Deep Blues victory, everyone expected the gap between the humans and machines to widen further. However, over the next six years, until roughly 2003, humanity made its last stand.

For instance, in 2000, computer chess engine Deep Junior participated in the Dortmund Elite Supertournament and scored just 50%. In 2002, new World Champion Vladimir Kramnik drew his match against computer chess engine Deep Fritz (despite a catastrophic mate-in-one blunder). In 2003, Garry Kasparov drew two matches against Deep Junior 7 and X3d Fritz.

Alas, this small ray of hope was quickly destroyed by computer chess engine Hydra. In 2004, it beat GMs Evgeny Vladimirov (3-1) and Ruslan Ponomariov (2-0). Then, in 2005, it destroyed Michael Adams, a member of the world top 10, with a devastating score: 5.5-0.5.

And in 2006, Deep Fritz drove the final nail in the coffin of humanity by beating the World Champion Vladimir Kramnik 4-2.

The 2006-2017 decade is the golden era of the computer chess engines.

On an everyday basis, computer chess engines infiltrated all areas of chess from broadcasting and analyzing to playing. They became an integral tool for any chess tournament player. They raised a generation of strong youngsters the so-called computer generation. When smartphones appeared, their Android and iOS versions were immediately developed, to the horror of any tournament anti-cheating committee.

World Chess Computer Championship continued growing. Due to the prestige and money involved, some controversies ensued. The most infamous case is the disqualification of the computer chess engine Rybka, the consecutive winner of the four editions between 2007-2010, due to code plagiarization.

(Source: Rybka, The Worlds Best Chess Engine, Outlawed and Disqualified)

Apart from the World Chess Championship, a new competition was introduced in 2010 Top Chess Engines Competition. In contrast to the WCC, TCEC features longer games played using high-end hardware, which leads to a higher quality of chess.

The human-machine matches proved the gap is widening. Over the decade, a number of handicap matches were held, in which engines gave various odds to strong grandmasters. The results were depressing for humanity. For instance, in 2014, computer chess engine Stockfish defeated GM Daniel Naroditsky who used the assistance of an early version of Rybka. In 2015, computer chess engine Komodo played 6 odds games against Sergei Movsesian, a former top 10 member and crushed him easily. And in 2016, Hikaru Nakamura, a current member of world top 10, feel down to Komodo as well.

(Sources: Man Versus Machine Historical Archive and Komodo Beats Nakamura In Final Battle)

In any case, during the 2006-2017 period, classical computer chess engines dominated. Until the end of 2017, nothing revolutionary happened. Their strength changedconsistently, but slowly. Everything seemed familiar and nobody expected any radical changes, any major breakthroughs.

Then AlphaZero happened.

On 5th December 2017, a group of scientists from Google AI company Deep Mindshattered the chess world.

In the paper titled Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm, they described the development of a new chess engine, AlphaZero, based on a completely new approach. Instead of alpha-beta searching and linear approximation function for position evaluation used by traditional engines, AlphaZero uses non-linear approximation function based on a deep neural network and Monte Carlo Simulation. As a consequence, instead of brute-forcing through the analysis, AlphaZero is able to self-learn chess.

The team tested thestrength of the new engine in a 100 game match against the strongest classical chess engine available at the moment Stockfish 8. The result of the match was staggering +28-0=72 in AlphaZeros favor. But what was even more impressive was AlphaZeros style of play it was much more intuitive and human-like than the play of the traditional engines.

The reactions to the paper were mixed. Many chess players were amazed the mighty Stockfish suffering such a defeat was indeed a miracle. But on the other hand, there was a lot of skepticism. A lot of criticism has been directed toward the playing environment of the match Stockfish ran on inferior hardware and played without an opening book. One interesting article on Medium was very careful to label Alpha Zero a scientific breakthrough in AI.

However, on 7th December 2018, another paper was published by the Deep Mind team, titled A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play. In it, they presented the results of another match between Alpha Zero and Stockfish. Out of 1000 games, A0 won 155 games and lost only 6. Even though the older version of Stockfish was used, it is an impressive result.

Irrespective of whether skepticism is justified or not, Alpha Zero made a significant impact on the chess world. They forced everyone to start pondering about what is coming next. They might signify the start another revolution.

One thing is certain: with the entry of AI, computer chess engines will never be the same.

The Best Schools: Brief History Of Computer Chess

Bill Wall: Early Chess Computers

HPC Wire: Deep Blue Inventors Win Fredkin Prize For Computer Chess

IBM: DeepBlue

Excerpt from:

History Of Chess Computer Engines - Chessentials

Talk about cancel culture.

Our calendar of events was cleared completely byCOVID.

Bloomsday. Get Lit! The Friends of Manito Plant Sale.

The Spokane Bike Swap and Expo. The YWCAs Spring Fling fund-raiser.

The Shadle Park Spring Craft Show. The Spokane Speed and Custom Show.

From our largest traditions to our smallest gatherings canceled. Its been a year haunted by the not-done, the rain check, the unperformed.

A year without festivals without Hoopfest and ArtFest and Musicfest Northwest and the Coeur dAlene Blues Festival and the Spokane Blues Festival.

A year without concerts without Cher or Allen Stone or Sleater-Kinney or Ronnie Milsap or The Flaming Lips or Wilco.

A year without dinner and a show. Without movies out or theater. Without The Book of Mormon or Jersey Boys at the First Interstate Center. Without Matilda at the Lake City Playhouse or Cabaret at the Civic Theatre.

Canceled. The things we do every year undone. The special events we planned for unscheduled. All the connections we make with our people unconnected. At best, we Zoomed.

A lost year.

It started a little more than 12 months ago, as it was becoming more and more obvious that the pandemic was big trouble. The governor would not issue his stay-home order until March 23, but the cancellations and postponements were already piling up.

Looking back, it is striking how many organizations announced that they were merely postponing things, rescheduling events for a few months down the road. Before long, it became pointless to keep track of what was canceled and what was not.

Everything was.

The big, broad effects of those cancellations have gotten the lions share of the attention, naturally schools shut down, restaurants shuttered, workplaces emptied. The major losses to life and well-being have been the rightful focus.

But theres been a massive loss in cultural, community events, too.

Almost all of the gatherings that signal our seasons and rescue us from solitude gone. Graduations. Potlucks. Proms. Weddings. Funerals in the darkest of ironies, in a year of such loss, even our ways of grieving together have been lost.

Chess club and Math is Cool and volleyball. Poetry readings and car shows. Fairgrounds and libraries. Gyms and senior centers. Climbing walls and rec-league sports and drinks out with co-workers.

Hooptown lost its hoops. The NCAA tournament was canceled, and with it Spokanes round of games. Hoopfest was postponed, then canceled. As the pandemic dragged on, a particular cruelty was visited on Spokane basketball fans, as the undefeated Zags the apotheosis of a decadeslong development of a basketball dynasty composed their perfect season before cardboard fans, in echoing gymnasiums.

The sacrifices were necessary, of course. The greater losses, to life and well-being, compelled them, and still do. And yet these past 12 months have been so strange, so divorced from the communitys cycle of life, that it has left us starved for culture and connection.

Will we get that back soon? Stand shoulder-to-shoulder at a Wilco concert, crowd into the Cracker Building for Terrain, see Cats again, swarm around the gleaming engines at a car show or see our neighbors at a flower sale or bingo game? Stay out too late at a bar, pack a table a little too full at a restaurant? Hear the roar at the McCarthey Center or Reese Court or Union Stadium?

Of course we will. Were getting there now, though it could not possibly come fast enough. The calendar will fill, and our points of connection and culture and community will return.

Well arrive there, in that life of the uncanceled calendar, on the other side of this lost year, as though we are landing on a lovely new shore. A place we know well, seen as if for the first time, with fonder hearts and fresh eyes and a raging hunger to be among each other once again.

View post:

Shawn Vestal: A year haunted by all that we did not do - The Spokesman-Review